{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 人脸年龄预测\n",
    "\n",
    "年龄预测，是指自动识别出一张图片中人物的年龄。（本案例仅用于学习研究，讨论交流请到[ModelArts论坛](https://bbs.huaweicloud.com/forum/forum-718-1.html)）    \n",
    "\n",
    "在本案例中，我们将对图片中的人脸进行识别并根据人脸进行年龄预测。我们首先使用`MTCNN`模型检测出人脸区域，然后根据人脸区域使用`SSR-Net`模型预测年龄。\n",
    "\n",
    "本案例涉及的内容：\n",
    "\n",
    "* `MTCNN`模型的代码实现和使用\n",
    "* `SSR-Net`模型的解析和使用"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 进入ModelArts\n",
    "\n",
    "点击如下链接：https://www.huaweicloud.com/product/modelarts.html ， 进入ModelArts主页。点击“立即使用”按钮，输入用户名和密码登录，进入ModelArts使用页面。\n",
    "\n",
    "### 创建ModelArts notebook\n",
    "\n",
    "下面，我们在ModelArts中创建一个notebook开发环境，ModelArts notebook提供网页版的Python开发环境，可以方便的编写、运行代码，并查看运行结果。\n",
    "\n",
    "第一步：在ModelArts服务主界面依次点击“开发环境”、“创建”\n",
    "\n",
    "![create_nb_create_button](./img/create_nb_create_button.png)\n",
    "\n",
    "第二步：填写notebook所需的参数：\n",
    "\n",
    "![jupyter](./img/notebook1.png)\n",
    "\n",
    "第三步：配置好notebook参数后，点击下一步，进入notebook信息预览。确认无误后，点击“立即创建”\n",
    "![jupyter](./img/notebook2.png)\n",
    "\n",
    "第四步：创建完成后，返回开发环境主界面，等待Notebook创建完毕后，打开Notebook，进行下一步操作。\n",
    "![modelarts_notebook_index](./img/modelarts_notebook_index.png)\n",
    "\n",
    "### 在ModelArts中创建开发环境\n",
    "\n",
    "接下来，我们创建一个实际的开发环境，用于后续的实验步骤。\n",
    "\n",
    "第一步：点击下图所示的“启动”按钮，加载后“打开”按钮变从灰色变为蓝色后点击“打开”进入刚刚创建的Notebook\n",
    "![jupyter](./img/notebook3.png)\n",
    "![jupyter](./img/notebook4.png)\n",
    "\n",
    "\n",
    "第二步：创建一个Python3环境的的Notebook。点击右上角的\"New\"，然后选择TensorFlow 1.13.1开发环境。\n",
    "\n",
    "第三步：点击左上方的文件名\"Untitled\"，并输入一个与本实验相关的名称，如\"age_prediction\"\n",
    "![notebook_untitled_filename](./img/notebook_untitled_filename.png)\n",
    "![notebook_name_the_ipynb](./img/notebook_name_the_ipynb.png)\n",
    "\n",
    "\n",
    "### 在Notebook中编写并执行代码\n",
    "\n",
    "在Notebook中，我们输入一个简单的打印语句，然后点击上方的运行按钮，可以查看语句执行的结果：\n",
    "![run_helloworld](./img/run_helloworld.png)\n",
    "\n",
    "\n",
    "开发环境准备好啦，接下来可以愉快地写代码啦！"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 案例内容\n",
    "\n",
    "## MTCNN模型简介\n",
    "\n",
    "[MTCNN（Multi-task convolutional neural network）](https://kpzhang93.github.io/MTCNN_face_detection_alignment/) 中文名称是多任务卷积神经网络，可以用来做人脸区域检测和人脸对齐。在人脸检测中会面临很多不同的问题：遮挡，角度倾斜等。传统方法中，大多使用机器学习的方法，而在MTCNN中，使用深度学习方法结合NMS和边界框回归，将人脸区域坐标和关键点坐标进行识别，相比较机器学习方法，MTCNN能更好地识别不同情况下的人脸。\n",
    "\n",
    "MTCNN模型的详解可以参考：https://kpzhang93.github.io/MTCNN_face_detection_alignment 。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 数据和代码下载\n",
    "\n",
    "运行下面代码，进行数据和代码的下载和解压"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Successfully download file modelarts-labs-bj4/notebook/DL_face_age_prediction/ssr.tar.gz from OBS to local ./ssr.tar.gz\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "from modelarts.session import Session\n",
    "sess = Session()\n",
    "\n",
    "if sess.region_name == 'cn-north-1':\n",
    "    bucket_path=\"modelarts-labs/notebook/DL_face_age_prediction/ssr.tar.gz\"\n",
    "elif sess.region_name == 'cn-north-4':\n",
    "    bucket_path=\"modelarts-labs-bj4/notebook/DL_face_age_prediction/ssr.tar.gz\"\n",
    "else:\n",
    "    print(\"请更换地区到北京一或北京四\")\n",
    "\n",
    "if not os.path.exists(\"./src/align\"):\n",
    "    sess.download_data(bucket_path=bucket_path, path=\"./ssr.tar.gz\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "if os.path.exists('./ssr.tar.gz'):\n",
    "    # 使用tar命令解压资源包\n",
    "    os.system(\"tar -xf ./ssr.tar.gz\")\n",
    "    # 清理压缩包\n",
    "    os.system(\"rm ./ssr.tar.gz\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  安装`mtcnn`,安装成功后需要点击Kernel->Restart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: mtcnn==0.0.8 in /home/ma-user/anaconda3/envs/TensorFlow-1.13.1/lib/python3.6/site-packages\n",
      "\u001b[33mYou are using pip version 9.0.1, however version 20.2.4 is available.\n",
      "You should consider upgrading via the 'pip install --upgrade pip' command.\u001b[0m\n",
      "Collecting numpy==1.16.2\n",
      "  Downloading http://repo.myhuaweicloud.com/repository/pypi/packages/35/d5/4f8410ac303e690144f0a0603c4b8fd3b986feb2749c435f7cdbb288f17e/numpy-1.16.2-cp36-cp36m-manylinux1_x86_64.whl (17.3MB)\n",
      "\u001b[K    100% |████████████████████████████████| 17.3MB 77.0MB/s ta 0:00:011█████████▉                 | 8.0MB 110.8MB/s eta 0:00:01% |█████████████████████████       | 13.5MB 107.4MB/s eta 0:00:01\n",
      "\u001b[?25hInstalling collected packages: numpy\n",
      "  Found existing installation: numpy 1.19.1\n",
      "    Uninstalling numpy-1.19.1:\n",
      "      Successfully uninstalled numpy-1.19.1\n",
      "Successfully installed numpy-1.16.2\n",
      "\u001b[33mYou are using pip version 9.0.1, however version 20.2.4 is available.\n",
      "You should consider upgrading via the 'pip install --upgrade pip' command.\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "!pip install mtcnn==0.0.8\n",
    "!pip install numpy==1.16.2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### mtcnn库检测人脸\n",
    "\n",
    "使用`mtcnn`库检测人脸，这种使用方式比较简单，但是无法对`mtcnn`库自带的人脸检测模型进行调优。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import cv2\n",
    "import tensorflow as tf\n",
    "import random\n",
    "from PIL import Image"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "这里我们提供了一张测试图片，你也可以上传自己的图片进行测试，通过notebook `upload`功能上传测试图片，并将`image_path`改为图片路径即可。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "image_path = \"./test.jpg\"\n",
    "img = Image.open(image_path)\n",
    "img = np.array(img)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "调用mtcnn库，进行人脸区域检测，并显示检测结果"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From /home/ma-user/anaconda3/envs/TensorFlow-1.13.1/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py:263: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Colocations handled automatically by placer.\n",
      "WARNING:tensorflow:From /home/ma-user/anaconda3/envs/TensorFlow-1.13.1/lib/python3.6/site-packages/mtcnn/layer_factory.py:211: calling reduce_max_v1 (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "keep_dims is deprecated, use keepdims instead\n",
      "WARNING:tensorflow:From /home/ma-user/anaconda3/envs/TensorFlow-1.13.1/lib/python3.6/site-packages/mtcnn/layer_factory.py:213: calling reduce_sum_v1 (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "keep_dims is deprecated, use keepdims instead\n",
      "WARNING:tensorflow:From /home/ma-user/anaconda3/envs/TensorFlow-1.13.1/lib/python3.6/site-packages/mtcnn/layer_factory.py:214: div (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Deprecated in favor of operator or tf.math.divide.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[{'box': [66, 68, 95, 123],\n",
       "  'confidence': 0.9999871253967285,\n",
       "  'keypoints': {'left_eye': (101, 111),\n",
       "   'mouth_left': (98, 156),\n",
       "   'mouth_right': (144, 156),\n",
       "   'nose': (128, 137),\n",
       "   'right_eye': (142, 111)}}]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from mtcnn.mtcnn import MTCNN as mtcnn\n",
    "\n",
    "detector = mtcnn()\n",
    "detected = detector.detect_faces(img)\n",
    "\n",
    "# 打印检测结果\n",
    "detected"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "将检测结果绘制在图片上"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=250x250 at 0x7FEA32FC7DA0>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 绘图部分\n",
    "box = detected[0][\"box\"]\n",
    "res_img = cv2.rectangle(img, (box[0],box[1]),(box[0]+box[2],box[1]+box[3]), 0, 1)\n",
    "\n",
    "keypoints = detected[0][\"keypoints\"]\n",
    "res_img = cv2.circle(res_img, keypoints['left_eye'], 1, 255, 4)\n",
    "res_img = cv2.circle(res_img, keypoints['right_eye'], 1, 255, 4)\n",
    "res_img = cv2.circle(res_img, keypoints['nose'], 1, 255, 4)\n",
    "res_img = cv2.circle(res_img, keypoints['mouth_left'], 1, 255, 4)\n",
    "res_img = cv2.circle(res_img, keypoints['mouth_right'], 1, 255, 4)\n",
    "\n",
    "res_img = Image.fromarray(res_img)\n",
    "res_img"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### MTCNN模型实现\n",
    "\n",
    "#### MTCNN 流程总览\n",
    "\n",
    "MTCNN网络：\n",
    "MTCNN网络分为三部分：PNet RNet ONet \n",
    "\n",
    "![MTCNN_architecture](./img/mtcnn_architecture.png)\n",
    "\n",
    "卷积网络生成3部分结果：人脸/非人脸分类分类结果，人脸边界框以及人脸关键点位置。\n",
    "\n",
    "数据依次经过PNet，RNet和ONet，每经过一组网络，就进行一次nms和边界框回归，最后在ONet网络输出中获得检测结果，人脸区域坐标及人脸关键点坐标。\n",
    "\n",
    ">NMS（non maximum suppression）非极大值抑制\n",
    "当我们进行人脸检测时，可能会对同一张人脸区域有多个边界框检测结果，虽然这些检测结果都有很高的置信度，但是我们只需要置信度最高的检测结果，所以进行局部最大值检测，将不是最大值的预测结果去掉，完成边界框筛选的任务。NMS被应用在很多目标检测模型当中，例如R-CNN，Faster R-CNN，Mask R-CNN等。\n",
    "\n",
    "\n",
    "接下来，我们使用代码搭建`MTCNN`神经网络结构。\n",
    "\n",
    "我们将MTCNN的实现分为**PNet**,**RNet**,**ONet**的顺序进行讲解，每一部分包括模型的结构以及运行的效果。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from src.align.detect_face import Network\n",
    "from src.align.detect_face import rerec, pad\n",
    "from src.align.detect_face import nms\n",
    "from src.align.detect_face import imresample\n",
    "from src.align.detect_face import generateBoundingBox"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### PNet\n",
    "\n",
    "我们使用全卷积网络：Proposal 网络（PNet），来生成人脸区域备选框，然后备选框通过边界框回归进行校正。校正后，应用NMS来将高度重复的备选框进行筛选。\n",
    "\n",
    "PNet构建代码如下所示："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "class PNet(Network):\n",
    "    def setup(self):\n",
    "        (self.feed('data') \n",
    "             .conv(3, 3, 10, 1, 1, padding='VALID', relu=False, name='conv1')\n",
    "             .prelu(name='PReLU1')\n",
    "             .max_pool(2, 2, 2, 2, name='pool1')\n",
    "             .conv(3, 3, 16, 1, 1, padding='VALID', relu=False, name='conv2')\n",
    "             .prelu(name='PReLU2')\n",
    "             .conv(3, 3, 32, 1, 1, padding='VALID', relu=False, name='conv3')\n",
    "             .prelu(name='PReLU3')\n",
    "             .conv(1, 1, 2, 1, 1, relu=False, name='conv4-1')\n",
    "             .softmax(3,name='prob1'))\n",
    "\n",
    "        (self.feed('PReLU3') \n",
    "             .conv(1, 1, 4, 1, 1, relu=False, name='conv4-2'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### RNet\n",
    "\n",
    "PNet生成的所有人脸备选框都被输入另一个卷积网络，叫做Refine网络（RNet）。RNet将大量错误的人脸信息去掉，同样通过边界框回归进行校正，以及通过NMS进行筛选。\n",
    "\n",
    "RNet构建代码如下所示："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "class RNet(Network):\n",
    "    def setup(self):\n",
    "        (self.feed('data') #pylint: disable=no-value-for-parameter, no-member\n",
    "             .conv(3, 3, 28, 1, 1, padding='VALID', relu=False, name='conv1')\n",
    "             .prelu(name='prelu1')\n",
    "             .max_pool(3, 3, 2, 2, name='pool1')\n",
    "             .conv(3, 3, 48, 1, 1, padding='VALID', relu=False, name='conv2')\n",
    "             .prelu(name='prelu2')\n",
    "             .max_pool(3, 3, 2, 2, padding='VALID', name='pool2')\n",
    "             .conv(2, 2, 64, 1, 1, padding='VALID', relu=False, name='conv3')\n",
    "             .prelu(name='prelu3')\n",
    "             .fc(128, relu=False, name='conv4')\n",
    "             .prelu(name='prelu4')\n",
    "             .fc(2, relu=False, name='conv5-1')\n",
    "             .softmax(1,name='prob1'))\n",
    "\n",
    "        (self.feed('prelu4') #pylint: disable=no-value-for-parameter\n",
    "             .fc(4, relu=False, name='conv5-2'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### ONet \n",
    "\n",
    "ONet与RNet相似，但是在ONet将输出5个人脸关键点位置，全称为Output Network，作为最后一层网络，将输出人脸区域坐标以及人脸关键点坐标。\n",
    "\n",
    "ONet构建代码如下所示："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "class ONet(Network):\n",
    "    def setup(self):\n",
    "        (self.feed('data') #pylint: disable=no-value-for-parameter, no-member\n",
    "             .conv(3, 3, 32, 1, 1, padding='VALID', relu=False, name='conv1')\n",
    "             .prelu(name='prelu1')\n",
    "             .max_pool(3, 3, 2, 2, name='pool1')\n",
    "             .conv(3, 3, 64, 1, 1, padding='VALID', relu=False, name='conv2')\n",
    "             .prelu(name='prelu2')\n",
    "             .max_pool(3, 3, 2, 2, padding='VALID', name='pool2')\n",
    "             .conv(3, 3, 64, 1, 1, padding='VALID', relu=False, name='conv3')\n",
    "             .prelu(name='prelu3')\n",
    "             .max_pool(2, 2, 2, 2, name='pool3')\n",
    "             .conv(2, 2, 128, 1, 1, padding='VALID', relu=False, name='conv4')\n",
    "             .prelu(name='prelu4')\n",
    "             .fc(256, relu=False, name='conv5')\n",
    "             .prelu(name='prelu5')\n",
    "             .fc(2, relu=False, name='conv6-1')\n",
    "             .softmax(1, name='prob1'))\n",
    "\n",
    "        (self.feed('prelu5') #pylint: disable=no-value-for-parameter\n",
    "             .fc(4, relu=False, name='conv6-2'))\n",
    "\n",
    "        (self.feed('prelu5') #pylint: disable=no-value-for-parameter\n",
    "             .fc(10, relu=False, name='conv6-3'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 数据准备"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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fcCLmZO9Lnl36V2Z3b62ZWbDnzZauc9RgAZxOp7v727v725SlDJmL5JxFRFIcmL5SdcjJ5UzAXwn7oDXNeJtzcnZJ63GxbYIf9H3v3Dv/EXJuf1PrTyszxfooQH55or1/gb7/1d0pOnceX5/MAWIygNyNIUQOc3Wzrh0AhDEkocS2zHe3b+7evPrisz989ccvvvv6m7s3r2/v3hzv7wJa6Tq3VgFIIiInQm/W+loo7X21cu8OgDk1VZHMxAgT9SjEem0NWLs54lgIh2oGVVMHHM7uMDPrtl612CNMSURSKufO1Nond2ISc4pIqbW1Lpbzw+u72xevXxh1iEFA5CKUs4B8Y3wqwOTOdO53OpcF2C+rUeF9zFci/mVXAH30qP3e+/V3Y+v4rzXvfbC8ekEU85WY/9br/7jLSRcNnZsLUQDuylsqZlB3T+yRQYKB3m7fvP7is99//dWXf/jdb7755o+vX72s8zQvpzrN7kpE3RWAiLij9xb5bjjXMPfetTXvvROJiEgp8WHcXd37CvW4u5N5YCxm9njxohvEYYT4oOpwAwlFDY44EVGgN+4Otq7We3djIqgSthKUAd2NEuU3r168uDKvLNHrhDGn/TBCO1kOU3X36A/ZuGQBIjG8n/tY3rq8DicQySX54m857P6zrHTRJfC4fnTC8XFCgX/Yu59r/h9bF+/7+AHCUt2V4Ga6ZWxKjLzmq9qn+fXr11989vtf/+o///jF599+98397Zvp9GCtdm2uBpi5dzVmFvK++HGeVNuZ7rLaMQknzlwigPGwS3NV6916jxItAFrN2snBtrXp8SYKQOD4MsIJ7KuUAIWVU++9RSrJFhhUZAhmAKf1MvRO7EudHx7k5avvajuZNSgSY8yllJKzYAVAE5OYEUUECGZ2kUwECSpzuIy379WGFPAGqf2D2zr+BBWx9y4KXfyJyxd4/9Xej+nfXxdPukykDCCQYyvXAJC1b0vh2lu7e/Pqj1999rvf/vr3v/31V199sUynVufWqrZFtZWcRah3zVx67/M8RxDCnAD03piTk9EalPOanjqbrylt7967qyL8OSHenoUTAFuNymFGBF2rrVgxkvW4WnkMfrGmquNIKWeDmrJw4sd+pfWt5/l0e/t6WU4gzVxKKfv9PnB5MxPJQmm328Ghek54EpEx89lpuDs7+0r4dyKyC/2C7XZ8Hx31Y+bxdwFBxkr+VrR26VA/9pR34MXthm6v8Ai5vBe4uDvIaYO9vv+TbdiCnV+V3cGO3pPwskxlGFQ7xObT6c2b13/88qvf/PbXf/jtb7755qu725e9N9PW2gLrzGxWVV1VY7s0VXencxsfiTmSFCJ2AlMqImZorbV5CdSltda7ubuISMrnVNXd4UzsbmYWp5ATwSmuDiuc3InTdjnWvRSkAxFEEOWX6CFz793MQaiVgP7iRb25uSb2Me1ylnEcg9VzOBx2w34ou5yzSBKhrUdljbLibVdOG599k5sZ+PJ2x9nE33P0vs2KezTxyz/ff+Tf1PooEPkjPu4Hwhh3vUgx/5QvfI6jNqCNHQa4W+fE2iqDzPp+LIBrn1++fPnixYs//vGPn332+89+9/uvv/nq/vZ2Xk7M7NpVG7kSiZM4HOTzUiNKWachrLAdIoqBMwFE4k5L6/Nc6xIxvfcOd2IW4SQsOWcA2xYKUAVEIKyOk5zBBHcmcjtfC8bFUEt3J+8I1k03OIJLQ8Tu5q7eyRopqDnmJFnoO3zLIAYt0+l4/3B1dXV1dXU4XEdTSErMSAATOISfmm1Ntxc3JBKryxu/8pt+yp36Hnf+t2nr+J7W7I/9/kJk4mPLLnGVy1T1DEq+daU+DAZs0QsAN7gCllhabzkLXFmG5fjwcHf34o9fffHFF7/93f/57LPPvvrqq9vbN2498jmsQSuIoAAIDkgOVCTFkWFmTiCs4Lo5FA6De3j0rl2D1RWbJKWU8xDJsUUusNGzotjkLohTj0PFCWxk8oj1na9AmLtAzNB7U3UgEgki0+h77W7c3My7krv33kPlqbV2e3v75MnLm5ubp0+f39w8TVLG/WG/O4zjPueBKUXM4heMmstcNU7f9YD66WHI312BKVayDw+5+BFm/QM9BOco8DF0CaAM50vzoctMRKudrq9gcHVXhltv5EogNz3dv3n13YtvvvnmD7/9zy+++OLzzz9/8eLF65cv53lm5lyEKDnMw9s6MRhknkQ4n/lVvbVoeWZJEXyrWu+6xiVq54/EzCkYBCnFyXBuKjo/5vIEj6qpEcRZ3eiCSRbs+3PsvuYC6qoQOMiIlJjdzE3NvPfuTqruatqMnaMUFQ1WT58+XZal9sYi19dPnj//FGCRTJkAUtWzy37HFoloQ30fUfl/+PXTcfcf2SnzyE1Y0QN336of/J4buODtrAoBTh526jAXIlfttTG59eba//j5Z5999tmXn33+2//z6xcvv339+vU8z2bOLCJMnMwpsGd3goMcTAmEbgYzITFzdVJXdna33jbWF1HrLQi9Bheh1XpFthDI3V21h7m6axSU4uNLVK2EicSJzAymUXZVeHdTU1ubocjdTUEEcgjgDrMewgSAUxDm1RzkQIe599P9ybsv0/Sw283zHGSepjbP89MnnzZzJ6Yke2awmDsip2Z6X36H6Kc1J/yYdAvfG+T8Fdalx3n/X1NAEz9lnV/lvSyejCg89wceRoR3kPht8ds/GwBiMMBCDECETA3oXWFtmpeH+9vf/vpXv//97z//w2fffPPN3d3dsixm5kZMyclVg73I6m6ubAxjISEiTkwiJEwEsuTqrfdgLIokZpZNUcON3GgYVkrMWffCzNyawzycMYeLjOIAVupvREruwYA0s2b6SIuPTsLVOB7bus2MCJsyyHox3V0VRITu7N6oEVGwO3vv0TZ+f3y4vn7y+un90ps5wMKSd7tDLtKcwEybyg3c+SInfh8X/q+H3X8jgfsHg6v/eqr6YejqAth6az5exCoAb5HM2dYvjJ48yiTMIDeHu6vAFfbq9etX33375Ref/ebXv/zqiy+/++67Vy/vlmWJAHoFzjtU2263gwQmTyAGpajvFJH18zgDFiVMs46ItClcc04Cgrp7zszMkJVRqKrm6nAm81XfBwBEtjgNHEFLFKTO5h7BuG29rUA4BRAXZiZaJbLW0tSq+OTRFsgOIpCIuqeE1poqq6oBrbXTPN093F8/Pd48nGrXHpiTZE4yjntbeTLBKHUgsvEP6xWQ/xRv/3e4Pura/+Qj6WzoWzEyShjRhBGJU/z+8knvCsERUUgFublrM+2A995evPj2iz/87le/+M+v//jlqxcvj8eHZZq76VpIZI57a2bdIbFrmJhYOAsnZ+rWo4POLML19akA3F1VCUJEwYt0d1AjcvJok4sODfdNwC0+JBGJcJBqHHkFFoPObhYB+jnQ375aXAes+8DXj7ISPi/7rxW6+mMFaFl6HDXmQrIS61V1bv34MC2t97ZK7/Xer65udldP4q2JiPD4hYmIPYJM/KSQ5u96/dcpYhdCAI+SD5GZRaUmv/N49/Pl5cc/t5SAkJigWqUwWW99YfI2nR6m06sXL377y9/88hf/6z//9//KiR7u3rTWau0rosykqs0URJTETLNwYmJOnBLn7EQb3fyRCBC3X0rqvfvqcTtxnARMROhdtWv3rTePmcmIzMBEJJJziRMhvoLqbAbV5tq6mloQuFhXh23veBKmbmbqcMf6ygQnCqfuDjW4gggGMiA7s4CEvMPnGsiSw5r13mvXatYlkRARFP/yryz9+upJkVE7mq0005yTw0KdiYlClX6Lr7bUFmdO3lsS5tGRGIezEeRvI3R5f304dv/zvT6/bfHnt/0wIf7dtT1MVaOoWWtP7IkFVud5/uLzz//Pr371q//8zy8++8M8z8del+nYezeLeIzMXFV7mDs858zM0YoRflc3wnqwwXBRHwlvvUXPb62uqqqt6Qo4hm4jwBy+/BGT8XDkqtq99141Ih+K3Rgt5FHSjJorO0ABHa00GYXzClh52DeCvs8rzxGAEdxJVso7egc1NtdkpmruNAxvXr9+eXV1dTgchmHIOY/DPufB4dAI5AlmIiG09zaR5iNB7D+IUNNfuHmPftwpuRFvKNo9ARjMDUbCIni4nb777rtf/vKX/9//+T+/+uKL+9vXY8nLsnSDwondHK6mblW7qhIzE4ZhWJUaA3PcqI5B0zUz2ZavbIIPzODe6AO9ta6qRLTRbtf+oDPrzcy0u5mF+EHvPc4QkECSMJu6kYEpQhMPQMdciBTrkAUKuT4CSACCrq0hTKAoHG2MLnd3YzM0Na+VO3tBduo0T9N0f3v3ev/isNsPJQ2l7HbjOAwwYTgYIiRCKyTguATmL27dD0XxH2/N+VtefyFzP59+kY695+DXi2UX+e76AGFE/peYmDHP85dffvnrX//yF7/4xeeff368v9duNBAnETcA3aMirmpbvBEweSqBeKzASO211lprMHLDJUcjUrhkXBrxBWPMtgMhToAt7H3EUoPjq6a9r3sjgvXoW2VOzkRgYwUECieYm58T60C917xVzi7WjdTWYhuYhbcyMChy+YBvYN7744mUUrJW23Q63d3evnwxJhlzut7v9uM+pUJIwhT/hyTZGnBabLAf9k1ncYk1//0bDWQ+uv5a+u6PFn/25WeLxzvzbXpvJSGX1Jb5m6++/F//8e///u///tvf/naaprCGu4cjuXezrt2NzUx9DUuZuZSShjFMWVV701rro3IvrYThs4m8FcRH8rf1arg76WPkE7g7M4M5slvbElC/WABEMhERJyM2dYMTSYTH5m5OgdDEU4l4TWBDats9amxO7LQ2UjmzRdBl4NAqXl/EnZzIp9bhlpOga6/z6eHutqTEth/K7c3VYbff769THsRTRE9AiKqtn3jbvX9/DvsnrT+vithl+M7vhnwftHjgwujjJYxcibgt9dvvvv7Vr371H//xH7/+5a8e7u5yzszSa72/vx/H0rVp65ELxlNFKCSKhlzcPYpFy7LUWiP4dndiO7O73nHqZ88akU/8q7gRUc55NXcRZvaVL+C4MPEVGooEliPbFXczWFePLtXuZk7BGfaVuhK+nSyoNWsKsMIlBCYmAvsqQOlGJhDAyQgc4KIDJuTelbpZ79panabT/X0Rub+5uX99czxchf6rs7AXBmmkwTETypnIieTcZXCBxb9zH9/Ci4G/M1DnLy2J+j0Wj7eM/vwQcsBabS9efPvrX/6v//Uf//6H3//u9u4N1EMVvZutCgPdm/aohooIZEX4okrfe9NurbVlWXUEVs31DQGMcCXkGiPswVZgOueyAEIBJjqPiCiGZ2yC2rb26ZlFBBxBVDzR3RXRumGtd4C7ra3Z2zeNgEACqXL1DSA198hOQUSJ6ExddKwyUmGaUcMwN3Yv+5JY4K699nla4BNTSXi4Pbx5sTvs9jkNJWUjpnXGoMMMGuR9I04M0Iez0q1l5+/f9f85VMTeWu/gM+89jC419j+gRw5Xt7bMpz9++fmvfvmL3/3ut69evfKu7j4dW0pJ1VJK3a1qr02DOEDEEsCFIWYN1NDLq7XW3lo3IMEJQmklJJ6j86DQiMgq8niB2xBRkB9LGQLe6aGKR9hQ9VUuxgnYHLuZqZm7dQ9z1967s7jRucwUaBJFI0bALO5qpqpb14gTQWQlrJ/jLoJHBsFMMUdKnByeJTGRtV6neYKbNkLPbPdXhzfjcH19fXN1VXc7InF3IXemlazjTiRxa4jSB931+4b+95mp/kWnd3xEaJyIiFejBDAMg3ZvrYmgtVYEsH483n/2h9/9/ve/+/yzz9o8EXHvHY61259I1Ryshugi3QKVRBQyvNZ7X1prTXu3IGgSItt71FU8yyQFvfEM4wA4C1jzqiK89lKYr6Wmlfq7iYc5IUIRDxWk3lvTZq7m0eRBTk4rfLleobeD/sgDVtGDFeIEzCBMcGKUlJdlSRwEG+Lg1pgRpyxsPUj2rr3PR+11JteS5Hj/5m4on/nvxrLbjQc3evp87L0xs8HdlFhEyKy7ixR53737tt/On3m9j77+/vxFzg+jC7bcf9f64Af4c5j7eZuvYckWw6wW/yEXjsczXVUdTuwgM+/TvNzfvvn8s9//8Y9ffvft129evui9J5HD/jowkG66LEtrtbvV5kOiYLOaO1kP3ASb8453WbndZCC7RB5LKQHPB5xyibtjy02JVnrC5TrH/SKSEkdpM2hlU20rdtkDaozwfJXoYH60m4jR1el8zpCvpx4RUhS0HImJAYYLedoiqWB8kXt3ZwcBWlsnZyQiNnhb+gkPQpTE3ex0mq6ubna7/fNPcHV1lYcCQEA4J9/mbgo7c90e7+3ZiV8a0Md+Pq8PVnk+9uC/2vqzevdHvtE7Fn+5oqeTRM6C6DGn1wGYdYZP8/Gz3//uu2+/mR6Oao0Jm0XCnVrVOYYIMFjWy2cW1cq4xIqIwtWjr5RWsFlSSnF/I2ovpZyhmJXZonq+H4Hr5Y0cdjb087/SSgZgd1e1S0hH1S30uBhRnd3gHAryipmD3NzIOSL6qG2u2pJEDBIRJhdhMgeM4YnJ1YU5ESVmD6qGOxGp2XY+RIzVVDsRDaOI3LZqL7759ub6WcrD9dMnnCQlImGOZJjZrLvCXXkdVPtuFPoh+44KwN+T1PZfe9Dk+ewupQSoXes67IWZ3G1eHl58+80vf/WfX3/5xWl6EGIWJqJpmqIPurWm6k4QSUKwboFiMB4xQTj3bm6Iqk2wDtcJAoLw6BGinD19ZKhRS4ptIyKllEHWJOR8WItIoEBmFqatGiJKcTis438lwhZJzEwhoiZEFH2I7m4whRnMyQ3mzGB+nJzIcBESMDN3a2TGECFzRhIqWVIS63AlcrCzQwCGend3b9qbu7fW2lKXsjCl29vXL158N+4ON8+eJyl82MfOp010DAHJRpvLmdu38QXWdJmc/Mzz+yh26X+rrR7/ZXN/J2F5z8Gfv/kZ4Y7QdxjKOeoAIIkc2vpy/92L3/3+t7/51S9fvPw2lHhLYu0Gs9ZVH5GNCD2dN0OMY/3seLaWTWwsLifyMJ+AUMLZn332Oek874SccymlyKOIKQCKUJdAJK21vtZcW9t4NSEzRgQGiGMAmjivW4h9hbvJjc3I174PApggBA66LkiSrPRncoOaOVwTwYVy4px4SFmJ42ByfURXTc3MeodTL60/nI5gMcXLly/zcCjD/vrps2EYJHOmklJiTvDODjgkWgk/dJNX0z7j848xz1vV6Pd/+Jtaf7K5fw84c14fsPizf0dgfIkcHGFDrfX29vYPv//tb3/9q+9efPNwd8vMu2EopVTvQAQbrnAwkcONzNWNz93hbnp5kYkg4TKFztZAj8zylcV+Rh7P2yAMfZ2d5NW3IisRRcMbtpmq52heVfsm87sSi8N38tv1LLNA4NkUMAfYTTZbFyZmCna6MAnBrJOTRKq6lXRTkjGnIefeyXpeNPAlyZRZQhjTADVD0I9jQ97d3aXyYn+4efrJp4fDgUV2Zj4OIrYNwVzjM5zB99XKz98awPlWxiPgF5MffRMV823u6fvrHyh2j/VWx8Blsd3PxNewOZa1syGC6ZcvX/7mN7/+3/+f//mLX/zidDqpatBy48EXhyPHnEgK+bxVISO2EJ2JxcwgAgtSSpzk3It0vjHngn9UW1dKjEhKaRiGYRgirD9zbM4AYlR2VO38e5xrTO6RjGbmCGOYGb7Neg4CDELxZh2dJkEKI8SDg9wpIhwBhTkLEgGCocTASk8p7caxlKI9B/Dae0+U1ndzIRKitpEpEjODqfd+Op0eHh5ev359dXXFQW9mKqUwp/DWUTHG6qhW5mMopm42vfKgPNpggY9xa/7BvPuPXeftfnauK+xtjS2fbWieT99++/VvfvOb3/zmN1999RURlVKy8JnPGLmmua3tHqbRpiBI7+lgnS2eOXEpRXJi5jB6NztTZZZlCXIBAFWN32/91zliX96inbec9IVfP59UEJx3JjPjLHYAW4fXkAm5ETH5OYfnUDUObXhyIk7MIqQKh8INSCxg0KYMSUnymNNQBmXvS22SoCHJZA6PxpK4FML5nWit1no8Hu/u7g5XV6WUPJSUIjs2gnwPqe8yFnd/tPOfau7/vTF9+nB/9MXP737q7VyjTavhEnAFYNbdnC72UXgRYlZVJ0JKbr05ptPxcDgQ+fF0//sv//CHz3/7i1/+xxd/+M109/rm5qYMwzJNWeHTMsBdNcGU3NTVuPtoLupIujBzWBo80HcwkBIRWxJOTEVESuYopqQ1P2utTad5aev4gCwpjuDMxG66zEQu7q0bQJw4hB3dXeFQVm1qBmxEGjclV1UaRzNzoizrIebdiJ3UKCQdoSDPQs5uBiclAoOJXBCkYoe6xNcgwFpOtM/5OmMoAgwAHcpY8sAl6dQsdXQwIiF2N6pN1YU5d6RFuORikMSlQHBa7M2x7R/sZpKrG2qa95mck2R38s4MMtq6EsEA1JUDCbBozAVzIpIQnApWD73dlg68i7s/WvmHZh1jOz1oy8Qejcr7OUagqCxs3hOPpHw8inB9r6TAT27eC8XZtQ53saJKj4hlVuwuDB3uj6fhmY1kZiLS69xa++7rr3/361/94n//72++/rrXNgxFtupPkFWmeakr9IFoztfgBkZS6ABblBtXIM+dZdWjjgoRzl7ZQyra69LmurTWwqOH0lykbrbq4q0lpNX1Cse1jt7xCMNE0mMQL+aeKmAGIkosRKRQC6Wj5IxV3/KtYJdhZmQAnBFEia1zQkRI4JrcxyGPQ9mVoSkTScmpJCGRlFhEWMCMwOdFiAN+JVqRYFMjg5iZLss0Lw9d5+Px9rpeDZZAHWCHuMOsgbKzbHm+K1agCfDYrnB2V/e1q5KENss715tsA7feMqjNLN+qRm25XLTSrER/962zkRBTwvGoZ7G1GHyPUX98/eRghtwJYm85fQJAspExPOaek0LNLDmbgpnOvpWIyGVa6n43aKve2+vvvv39L//PL/7ff//myy+fkF1f7QGQaUocW2jpbam1GzX31r137QChgQnWjYjVsaYBodW70tlzziULM8PRNtAQgJnNdVmWaoaUaHvkUErJksy6BhDOONPisULvACDw0DwIQw/dyTVU6+Yc+hlEDiaokKvbZgOBUFLIALiD3RTxH5Gyg4mNIITEkoVgyIRDyvuSx5JFiYjGnNIgRFwGloWkOaeVj6tkyYlN0qYVLMGF8db69HC03X26vt8/fX4FW5g6o5m6Q90I4G4OJydxYoPb2Vlbp+CcOnTVQmaAbYnS3qP50UescXWgsc8j5V2z39BC3PLfixchhK+kaG7c3Ly/g37+eDpD+tBUmbMNv/1xCQDEkl1AfjF2EUShdxv6/XGzHXCCEZwJwk6kpogJRw4ypd69VZ/nrz/7/OvP//Dm22/teNo/P+x2u9Pp1M0DNlFH67a0XjvM0W1r8fHVCzNcMglZYhYiYk8UGRpLivRupXO11mpvtir9mhlEKKWSUk6pcBICWxSH4psRJ4YQJ5boKWXyJOSSZVMwre7CdL5eQqyqtlIanc3g7rTuc2Dt0j17d1A1uBg5mxsIKkCWGJ4KYWemQXg/pn3isu4pCJuQgillSpnSwJzY3bsZXImVyZlJ2BggdpC6i3sHcW3H08PLWp+5T4S569S7gotwEclIDCe1bsQrn8wNBre+dZ+DnQwUEST8EUV4J8P5oEUR5XNaH6fEqguyeu6tkLf5cVvBT96Ogs0Yz2/6U/x8wsV0l/ef+dZvHAAEzEDfkq81lCdq2s3hbk4gCQqskDvUAuL2gDm6CRvc2IGufZ5eff3NL//j//f1H/6Qer3ZlTFTEV8YlNjBx2lp3WvXpmgKdZhjq8gQ3ISRM4achRASwUViglIAgSAimK80mt6DCdy6AYjCaikl5jaGKKQqC0Up9Py91TyU0YlYdDVcMUPrPTuBJfRL1nIm0LubmXZni7oMl6Hw1vd0Dk/NzA2JhQdoP2uVUUqrXg5g4n4o6WYYhpyYqAfbx7upC4FIc/HciQRV1bSpLmYqhMQpsWurngucFIuksttLLt766f7u2+Px6f6QRXxalLhIHksZjzatBWkENinuClMmF0I697CDmBMx77Yj7kzZOPuXt0x9u5rC+5W1sCpjuiTaotZ1z8Q2iKewjLHzicgQWoJ0+YLbeo9++0Fzf2sXXtLc+MO7xtWcQrgx5BT5Al8M8VkXcGjjm1vvysxwk43Rykzi1HqjRFbbd3/86ovf/vbh1auRxYm1Lw1IDCWqzVrrp2WdcBSdbCJRi2Ei9O7CyEnKOoFDyZzYJZQytiTBzbdAZmUWBL5+BteDyA5YN0+w2CkSUan1teQfEXwidqzYIhmTC0fdIMgI7roqYasBbjFHWER2OYcR9O5mjpVN4cRgJgaVmPdEFJT6lCPqQybel7wruYho74XdDOQd6hARdhGWQs4gN/Om1mGAgEmZkjtBrbu6wTESmdo8z3p7lx7uPtntk6MdZ3UkkiGlfMIu6AhGTNGPawrtTM7k7CuZohuIhGQ1d7/QFHnH3N+xy4yrIGZsQLCmlOLqEXvgb7Ef4nXSENOvBhGJJLRf6JD+VFZmYoed3djlDx9JVUNKLshTiPlbTA6klDRCMjcQRfNo7ysfnWggJpHMbIlA2mCe4A9v3vz+N//n/vWrBCSmaTo1b66Wy9ibLktr2peldScDiJHW7gowCGRwJEDgxM6BuvM6WKv3TqQgIXJ16rr1qppsBMeUciZJJFslyCUK6msBioQFqNXcjSmlkJInc1Pr6iaUiIWsA86bMgfYhdmZCcYbmC0iuQiZd4/mIyKikM2IkQWxN2kLvYiIiXPiRJKEdsO4KyXBuxFTUlWm6ONWFkgi6eRMQe0higuFxJJYWBLctXUI9d5rm51AKK3uptOb431x96YMHkC6kNxrI06UhCVjJQJ1NiUYXKErI6ivpW152CQyz4DJZex+CbPED4zTxkKCeUd8caKUOGXOOZeScpbz+YzeiUikMzOgHwiyf5K5v/+rS3W191fvnZkTC68VS4rdYqoRYYECPwsrM9n43Ii4GuRQ7Z0F1vXrr778za9+eby7S0IE6/OSBb3XMuxaa9M0dfW+QRnMq/zLZjYuhJSQhIRYyJ0SzCLWqLURxdkT5h59Gw5mkVzKkFbbYnc3InaHn3OnkErlM6YEdUQcDNKQoyESgTAT1gppdMIxyMnOUDoAEcksiWKgE69PFNnEw9S7mxmDsiTemmWJPec85lSYdsM4lCJuZC7EjUAiTPCIJxhMHlUtEfGuJJ5Y4n2JsxtUPaoK3XtykUTeW1/qfJpy2jkPZRCWQZ2ePfl0GIY87iRlP5eT4Zng2l3X3vZuK+TH+hiYvcOiO++B8wJgGrE7tpKfOSyiFxFKRSQnTswBIW8l8PPL6mUs8tMt/11zv3Dw60+8fe71r1GNJycic++tB1YVFhA0o9i+QpITLdE/AUqA9tp6G0RctS11XqbvvvvuN7/5Dcha67uxjGNh7iSyLAsAIlrmbhq8QsoprzURB0zjSEmsYTlC7Krx3kJcSglienc1RVOtUX5hcBLJiZix6qCTalOA3Jg8JUZKrozk4sTrcMmoPrKtEpOsqiQhw8ExXIRWMUqKiwSszRwppSGtkYw74SzbtFr2rqO6ezi12NiSyMxKSbsyjElKFGiNS+ZuGkAUMXc1YbAHAa54187VmOGeUhnzmHNSF/dVK8oJIjlmfuSc53l+aq6tXz19SpzLeEjDoIfnh/3VuD8QUVOHGsjIjVSTEEIZk0kdraqvpSk8WvO2VlGqbZ1jG21rJOPQlBJgrTWHEXnOknM+SxVFvisWfWSia+a/Nq99LM/8fpX19H4kY5t9v4suBY70ODTDTF1N3R1E7M68tvwmt+ilA3wYd9E2E6ZggROYJuIvvvzysz/8bpqmlFJEPnkcWBIA89Ah4oiY1gIpCxG59Zj7JUQBVBORBDedJZDmSIUIotata1ONGEwEyIVJ3M5q2A4A1okIpsIg56ZqIuRKntjNVYn5XKoMnxTnjIiQg1dFSGMQhNYg09yM3F2EV9JOVKU4Apl1nCBDuJSg+8pKFeaUOaU0JMk5F6ZEnABWN6gTuWmcSEFOZCIhZqKc0lAKAeQYYqYxxJlXnV/i3mxeWhHmsSxLq3Oz7olkTCPKLuUiUobd9W63H8cDkWQ3dxcQoaM3YlqtgxPczYwgUdo7u8IVRgAQkNRm5WcHb543Ok2InZhaI6LWarQax3CdFTzrnXWMl46dRURgsXfl6X/sSpe27nQhU/12hvG4aQQO6jEYxd1MyYmYSvSZucM6zKk7YHAIatgTi2CtJ0DVB+EvP//iq6++ApCHobVlmeebmxsiCdXpyPNFuDA7MUs2QmgnQQ3wIImkxIl4VbqTLV4iZPdgB9vSajV1pCSSEuUcZ1HcJALMlMxXCXkhGLkIrFdPrua0KbgHtYtIiGxTyZOV5osz5QYbkSuCNt8EDuLMSSyenIgyb4CG95xzYgnbzSI5i5Q8jiURM0fPn7MZbfQE8nXcGdMqfllYMjNSxuCJBUBmyXlILOypajWzrlS7+mkSxjjkhWU+tTp3N8l5pLxPZeQyEA/CA3EGAKMEInZ4GHGPczZsm0QAdn/EHDcBkHhMKMc/SpWE1cNzaERhbWzvCZnIUxkBW+2MGa7SGtVKLds21xbbjAb4hvxudukfaZ1719zPjwuMfP15o3p6RLQbqRZAJwJCnpzYEVSUYOLBHKZohrpY764G81mciMA+jiMnIQbY0Vtf6otvvzve3eecU2JVnZf2VKQ1692WHlghiQicDcShNqnqXc/0spxzWfN1JiNiYWLzbj2YYe7NDIi8ioLgznyGwGitfhusk4NjnjSxQ3soTaceTJjYIa32lBKTDEmIKFGMPorRjsTEEPa03uC4XO6eePXcITEPssTCm9hT71xSLikzDEDOeRxLQEbEMblPrXVszBx1Mz031LmAirD7Wn4WrBspimwRAlWFdifxpm7mfFp2qQxc5qnNU7cOQhZJJDnJIGXIuYASgu62tmsrAF8nPziMggrnTsSP8vBmZmrbjMSzLA9WOnTsAbh2pQ1618dgPMizIHYREKU4uUL2O2IlYaYNRNkYC++54+8397Otnw19/eEdzoOvHGcVcrVIy0BcpGRJIMZcoR1z1Wmpp2Ob5r7MqrqQQUhE2n4/7oc8FM7iS3t4ffvw5naZZgJ6NyeBcHdMzVrT1qytvUhhN2Zq6qbqbkZA4pXIlVMys42QzGamuo6JNLfzFyEGSQILwKotikyrYZo5lCP1Io4SojZ3clOWknPOEf+01gCEEh1dUF7Pi5k5x2BK9F4TMQg5pZSEHXA1OEOEJWUmcyXMsEG4ZGEkZgzDsNsPpZRUctAe0LUHRR5MDjVKMGhAMJTEigeH0TnkylK+qHk7YghrEYio+tIruc1Dr8WWRVs1QhbJq3ANXIC4kjCldb4UmWqvrS0zC3LODkCcJTfrfZntImI59zRGqhO51hmfcXdTmufKzOM4AsSUHWs7vIiEOj4cZq7dtNOjAorAyZjTGtLEQN2NfvtDAx03c38M2S/oNuePeAbL6VHmC4YAokEU0bKid7Taj9N897Dc3R3v7uv9/TLN1lULETmE9/v9br/f3eyvbg7d7f71G62Lxsxet5TSUHbzPC/Ne/fWNTQqXK1rj+qpbUVoEU6p5DQkycIcMY7TZh7dWlOn6k69qxsxgzcNdce6H7AqaIHd4RpKFjAndlN164q1CM85Jabu5t0jLAmtjggugbdAmJQzEZE51DqbMI+5pCSm6urBzc+ETEKJjEWCq8M05JyzDMMwjkPOGQnuTuYGJSUT8tDtjgyohXIqioqZIcHgLJwoURGFd12py10bMxUpnWypdZkn8lJrX5a+zF2rBu3InLQp2NA0pZbWeWnMzjBtXafTaTo+sKAMgzOxZEiqrSXQWYJK1+FqknNeU+7EYF4LEaq9a1368XjKOec8iIiZ9u7z3FR1HMe0yyIJRNa7qWvX1s3WGx/VnNBwhRGzPwYwP82723tx/wouRIjivjIVAlgnGBk7wAmA9u5zm27v59v7+xcvHl69qbd39TTZ0mDuZRUUP+1yHobD9dX8yRMSfPPFV21urga1pS0ppWE3zvPclVo3XW0dqmo9wmYE6y8L8yYOs4FZcAPYVbERBHro5TbtPXgfkty9qcN6793OsXvcVYIzovVCFTA1dXaIPOpzBKpcmM7vG8SEuFbni8bOTOykDGJIIsqSck5GbPCu5q6ClFmSECA9wcwEXpLsdmNMS5XMG5cKxOwMJyd4YrKgwQcnhymBignRSmdbO1lARD0KjapOYI1AQ7Wrt6rzVGepoyzzXGvtqzIJmLMFmsksQXIiEXRnR2ttWRZJJCkhFBWCRF3rWXkz/gzX/uzZs/WaYRXEaa3N8/xwv0zTdHV1FZcr0KrerbUuojmHVmukSAJwj1IdiVHkCWSg8BpG76n2/ZD+bjrb+mMMRQCQVyxtQ55DGQJQZ3WPpDZMTVXbsrx59erh1au7b16cXt3204mbsiNHnyVRd+tVTnI8TQ9LnYz988/+cLy7793cqdbGzOM4zPPczdUjrV+JQcHNMwMDlMHMmR8NPXaCe6ifB6vbVWOcEdZxjVvTWbBZosP0fH2I3grh4khxi+/9lqIBbzPeI5RfoYMNTQce+e6wQF3WuF+IhdGJlYidmEgYKSVykKAtFeRJuKScA7hx4yTuGuU0iIA4xLa1z2rNXBlp7QwXJGdK4kQaCDbOVstEsvSmtUURtpRC8GVpfYzJH3WapnmqVigl45VKvbVsuWMjys/zfDqdypDKMOScpOSUB4PnnHrPEY1E21ScflFIgWtc3F7r6Xh/d3d3e7ssy8LMqh79BcyrTptwophz4RRtjAQGCW0zbI2AuLwrCPijiANvmbsbg8mYGrm6gTyDCzg75yDFwRu0kjW2Tj60BW5jyqoqotSaLMvy+pV9+93pD19OX7+QbmUlzYLMspFDQdR0qd5rpRfH17PXrz//7d3td6YLkQ/DoEYPp+Y8uJ/MbAmlaM6Ws6N7rwwkwep2mBKMtEeQDwAuzAlUmnl3bi4ZuVmfqs6LpsSCQpTg7TRP4dBTsJRME1NOaUyFYNDelkYGScgZKXNywaLmbRiG/XDYpz11nlp192maiUhKcoVIEhFVZfg83ZtZNJ5mQNC8NQbIq3gLXxXEGIC9zyYqIkOmEuO1uyWnXR5yGXrv99NdbTNnt4K5LewG7dYaiSfOAMd4DjIyISJxGBwmknMyM2PM07zM1syZ+ZMnP7t/87LOyymfdmN5mO5evfnuX+v/EGGqCiNLA2QAp2WeiYhVE/MynXRpt29eXV9fH3b7pz/7Fy5jU31yuLHeAITisa/MMBaREoCycfA/4bIc67dfffft7f1Qdk+efbJoH9KhzjNS2j951lpzoBElFjNzhwyj1uaWHJpzHoZs1smjvHP24gnrFE/6MbNHkmxdzFvRZZPaNIoJzNhETiKWIBFWhMdKEFet03y8u7+/vaunqbeWV9nDGK7Ljm7wbXa6w7zNfe7TPM99qVBDSKCvyTARiXs3M3M+y5ViLTVHQZ4YFCAAEOE24OSu6k3X8ARBYDz7bN9IHb71o6x/3XpuzYxg8B7MvKD+5pwSrS0BQQRggWqL/MkfZ3hQ19q6m5lAoix1Zuxo60YuRNb1nLSFL4wDh5mLJCJyNWcIkXvk3HA/91zHhXJzDWltTp4lOaF3zK05uowll5JLAlF31NYWs2mapmk6zdWdSimPaSWCIbrUWmtbhmHnG2a4/vv5TzJ3X5bJWs8swzCwENjFoFvRJ4pKkfbHN1rrpszedTodj/f3r16/fDjeB6JH7HB1t2hdN3eiKLGtn80RoM9HlLku6lc/xqk/mnsiNfegECs5yNkRsoVkcZaujA4jBlFj0h6BDAtzbzrdH2+/e3X33evl9gG1szOxMjMnIjcnh3d3chhDe9W5T/enh/nhodXF1TaoKg5Pcvdu6F3VlLepWZu5U2KUlAzemxocFMUbNld3czPFRXPd2kCN7pZUidBNI/hzNQsNCX/cDEzRugFhpI2wsDYIkafEpSQi78t8nE5mNo4jiNRW97by+yDunnMGB2nMmhu5KkfhyYQJbqZ93ZDWAnYUYjOT8z7pLVqaklBKaVmaWYd7r83MiNbtZwozq3UGS/YyDEPZjUY81WVelr7Uh9Nxmqaldndi5taWDdfz3vs8z8uyTNMk41UO7bQNmF6Jf9vU8i1yQ0ocuEHAIywrMwRYFQCZnXktD4Ncrd7dv3n13YtXr16eTg+UilAJRVq3DpiIsDPnFFJC8QHIHWbu4YPOlm3bPiTA+DFMtx+Zq6Yzap9WdiOxOpFnIol8SQ0EQdS8UQkGb6olzoPWl7vjw8s38+s7mvtgVIjJbBUhhFNSCdUhUoICvc/L/PDQ5sVbZ4cIJ6Pqkdpb7da3eVrhecmdnFlWmjhFpcHVDZw2xMhczWJ2B4icmdRUzRwKsFHTHnp6KwEDsZmBNTEwZzbvMfQrZURjqLurBUhMoU5jZsuy1GkOmzYz1dVJr2wiyrzRhDxSbgK5xug7ghMEat517TRwzymVLMwI6ePExEwA1DrHqSJcYXGk9F4ZLkmGlIjgUJiSe5KUUiopp5RaN61tPi0Px1OtNc4xtdW+3Q3sqq31utR5WabT6TRedyLnAExtrTaktUt75TWEVZGb90bMxELkHBrdsZNFEAUlNjKDd+9ep9NyOk7TsffKDLCnJFlA3lUXODnYDMxps2ZiMufN4wLbD8KPGWZ0eLwjNP0jCMBxMjjcKArwbhSCynBzslWT2WHWwcw+8JY9Ejp07vV+Or150GkZ1XeSB2e15iBaR2JBYWTGUCNlOFrv8+JdySFMBlTfQAPty1IjfzUwrTPnSbChouauPbLAtc2NOWrqqtp7zPNIcT00ICWHAuhG5E01zCz0ZyJoodDi0xqtLsIIQJDYramaBidehFVjJsKi2s2sTpOZLb1t8YaLSEpRj9Tupr0xLAsH6gO3xBDKaqTmZCmxCEuRlCPEBRLLkAtxYNjdDJJWxkFvrdYFZinnYSgpM9SsNYemxIfDbhgHFmht01JPp/l0Oi3TbGFKibRV1bbUqWQWYTPtvdZau9bjfLzSilUZ0wKWABmFCboTeSImhMSrunbyBDCTY1W9VJBu5dIwLe11qbWeppNazYV3+0Js3SgnCFsMeGvafVFVNw2ZzhQpPwB2Yz+7c2OE2KatUI+vnbw/EoJczb1RMrjS2nkL95heF6oXskqIEnzT/OG18Yzd4NaWupym9nCi5tlpRBLCptDPsBZbyd3cVRgGJzVrlbQLSIh7hKOt165Ne2uqBiKJTmp3xzbEL4Lw6C5lIpLEzN3XKMgU3bvGGeCO6B0Ggxnufe0oDR7LNgONiTmI/a4NHLzZhNCOVGuqykzjOO52OwKm02me57osbtZbO26SqDlnSYnWIutGD1Rt8ywMKZkYvVcBNFEWJhdyCEMSDZJykmhDEeKh5FwSEZl1M1JrUMZ69PVaK7MMJe3G4oZ5mWvtmUV2+Wq/J8muNtXleJqm46RV11ZDESI07U5ore2HfUoSCmi91977NE29dyeIkBMBBlf2CGEd2zhYVa11nqZjHlJyA7G6JcvMDDUigkTwGRwHa3U+PjzUWpPQzc1VKeX+/n5Zliwx2RaAWesGrb0zJ2bO2deI48zDAXyNW8LWQ71MGIYfHOz+QXN3wGDmbLAY1ExgAwvDlGIKJ5NszN5GhLBUqKGrtd5rw9JYsgiJuwfvgJwdMDVftyaZE9Sth4A1XBk4A1ita+i1I2rsdB7ETi7AWXDGnRmcM8NdzcAh6K4aMomIDgtisbVZVDTouasYb2yG2JSUiJgtgcCeC8achsyrdiSUiEoZdrv9kIdlWW5v7+ZlijsRRRMR3u12YxnzUAKdjMH03XurS1uWJFTYOTFUXSChipC4JB5CqGwd3Loqa4+5JFl568Zwha6c2xi07SKccwoVqtYW7VqGXR7HlJKBamvLVKfTsizNzAQcA0mCEUch1k3RZG3uatZV+zyfQlqZmV3OdCmDq6lCeyDrZjZN0+vXr2tvzqJmKeUyhhQZlyy73W6lxznDTFtty+xmu91+HMfT6dR7ta7MJESZJYm4WgvOKTSlUqJRBYEhrNRIYAvoV1dv7LQ2WF6G7/gRuHv3YDV5gBkESYRMoG4x2tBD62qltQtbE3ThkoNyEkKMqzoAhzmamQgHC0Wtx3QUdhjZGceNm9e3v55XZOdOEk3A7r41j6oRxNE00D0g0BUiVe8aLwXFqnxCiNiYLMavR1qIVRKd3FZWfozbICtEY0njUEriHH1/Rsyc067kPXOq9Xg8TnVZAvZl5l4hA8Yy7ne7XAqAeZ5r70zugLXe28LGVsRXgCtSbc45l5xySiXnLCmIkIm4yDqAxKFkIRfs2rX3duZjboA6ubtac3dJNAyDhdZU1/PEtShGMjNzgtaL2kkoZ9qKb6nG4+PBUSUD1iGSajGcyhRujnmuvb8+zVNoeY/jOOzGLJJS2o3F1fZDERHkSGc7mTPzbiiHqysiurt9mNMUbBsR2bIw0+5EzhwEad6mzDJDKD6Lcxw0gJ07e7bA/Sf4+MQCMwU8kzNTEYE1Pc6uvS3NWhdI0MdIOKUy6X2WJAkYMmojNxFKJdNQVL31zokiE4ppROxovYPRelM2JZ+W08P0sCxLhTbzpj0qdt0RnEUA8I0YFCwgXhl2BmeGE3o3wNStdgrycHx9BtShqkyZODpeVdvWLU1wdyEmZjKNEmVKIkxDTleH/WE3DEO2rl3r3d3d8ydPh7JrTdvSHx5Oy1SXBUXAxZnw/Hq/O+z3+/3hcEhS5nluxqZN3QU0lmFfslt3hXpjQpE8juPV/rDf70OUeBhy4uzuAiollRKMCwWQEpulqt2qTsscpZnD4RB6T/M8t1aZOQ0p55ySOMTaOlK4tbbMNepKgDNjLEOtVVs1671WzoNb906SqLdlOU3hvN2p9y4iEbR2d5FclyWVXPL45MmTpc55GEVyt87s5kSOeV5y6kwkePBWxrGkyixBv+Ay7IZhIFAI9ZSUJaWAmUGUczGjq7xXR5JMYERbIKKiFLGCB0VeBNadhc2c1mmFj7ZODvgWm76nchO/SeiLuAlB2ApDzFGXNt/V+2OdTn1qm8BbqFMM/TmncS9jkJ6tZBnGMuzKlAjMRmhu5pGIdIOzGpmvLhTeTGvvVftxmWdoBaqZXpAfEkFBdi6oAuunl0RQd4DUViyAunvtatY1snqGB8mUxBHqkyFKqqRqvtZKYX3V5PU1DAy/Po7j4bDfDWWe53ZciIiSJBm0W13mZW6tuTV0AwFP9uM4jrsyjqkMnIRldu+ttXkhojIM+3HMwr21vsxhFyJ5yGMpYyklZEoSi4B81YlPOWdib633XkspEM45TQuFgELOeb/fJ5Za6zzPqppzzmUchgERoJvFRe7daq3dHJxwGCKTTiyhN29mQSc3EbrUyI4hDe7wwJ/XlcuYh3F/dQ2ga93thmHYhQREzjknrvPUWktMMG/zYnVZ1W+Yr3b7NBQh7q2Z9ziackob7YKHlIOj5qDVuAMaccLFiGIhxJwgdUMgKY/9HYYgs27rHVu//E3aUSfyTEbomCvabA93y5tXx9ev2zQt00wGpug8SyKi7ZlcXdXDzbivQGb0nIWzWGIzUoermWmc0JGFRh+AEZrpqc738/wwL8e2VFgFenwaJjG4u0iC6iaOt4pdqHtaWQJYBRrgaq6KVrsxDOA1OgExs4twNogbbGNWBqIdbGsOqoQDHVJ8yOnJzfX1Ybcfh5R5XixQxaA6nU7z/d3t6XTSjiTYFYxjenJzs9/vD7tdKUMpRd0e7rWejq562O+fPnly2O17W/q8tFpV25Prw37cXV1d7fe73VBYiIhEKKZFFUln8mC8L+cE09qhqi2m/zFzSgCa9qVVU9+lnHPmlEgkmJkGNrNuWnur3Yg0F0kpkTBzYqArrDfVxL7GsK62tRA8GgeBKSRRiVOh/eGJQK6urtx1JYRKWmWorNVlmh6OppVhy3xa6jKMJec8juMwZAwjiNFb7MnY2NEOlswklUGIOYNTzKYKh01E7moeajxv2S6tmeH5F7z9+UiA/aCDB5AKt5WHvMw4vvHbN6dX3z28ejHf3Wmv3jXaGAA2RXN/M73s10/ak+d4+ul4uJGcbp7snz5/8vDqjXfvCjYnJmKOrCWG68LF4Iva/Xx6fby/nY+LayVTYhATREzM1MyEQ/fcaKOlxUevvTE5P36Z0EaHEZtb2C8TiBGEFJaMzlV7rb3HfElBIhJj886AMAQogt1Ybq6v/p9//flYMgtqrVEpvLq6GsrudGz39/ev35ysYT/iap+ePbm+vtpf7ffXh8NutwoZLEtjM12WcRxurq6fPXnK5K/ubu/e3Kq1XclPrm+ePHlydXU15BS5ZrC5okdcRNx16Y3Yx3Ecx2Jmx+m4LMvSKpjzMJDw0qp1axqNv66g7paYcipT6xroE2KaCKmDYF67O2VwFLDDLlz7WPKQ1kqCqRJRzkMp47ylekFNAIQEqYw5Z7iSKQAIr2L1klBvyzCymXUxXaaHtkwP5GOWHTS5NaICkeQpcQdZFKpYSFVFlQjMeatpCZGujB33IPK9Za9mtNWhLq3/bbt/tHW/kPSJ5CdZb8IMdiyzvXk9vfyuvnnZb1/68V60U6BsLuYUY3JlGWHeuk1qyZD218OQdzf74TDQqatVMDE4pKbZXcEaQmigpbf7ZblfpmOvs3cjWWf+MolJ7wZVYnNX9riuvKr/R18mBegKAGarDkeIXz/m8DFgGuxO3bw1rbWb2Tr7hWHaCWBBYWTBfpeePb3++afPn1xfjSWZmdYWFFY4z/M8TTbVpXeUhMOhPH9y9ezpzdV+fxhKGVImWKu9AaqF/XpXMJQkpL1O03x/e7csy/Vh98mz58+fffrk6fV+HIk9ZyklpZQkcZKcUnocVkXGzGBStdrbXJemKjklou62tK5ViSjlIdJWkIRioJkF1BAds2tFmUS6MRmzqiqcEykzM5BZElMWTsQikiUVSXEzFCHFeG7sERA4ZcBhK5nUVwFYEjUIMUOtLtPp9HB7Ot6bLkmc4ZQo+whScFBUTRKlFHRsJ/JV7G8tlW4tBBsAbdbJo+OGyS1Sr3NC97atP65LW3/HzSeDCxy1+fH48OZ2fvPaHh5oXooFz9S5uUe40LubXklK08lUJ3NyvjYQD4fD7ubZzeT3rTc2B5PT1vrAKcionfqieqrLqffFtZq6MDOJsNtKEnaH9w5XWqt5Dlon64LJ4EQsIDNrHnqiCA0OsK6dhwaHknvXpTdq3XybtmSmcMiq9baqU+x3w9Prm2dPbg67oZTcWktJhpRPzK3q69ev54lqreOIm6vhk2dPP316fXM47Aa5GgeQtaXWZYE5mA77Ij9/PnWyrm9evlqmubV2c3X16fNPPv30+ZMnT64PVzkL4LlIKamUlEpe3Q95Fs5DMuuttflumpdlXqalNQvhSBYxi/CXNpnilArn5ES1NzAxEyVhZiOoau3dyXZp2AQemYnA0ea+MjeFU3SOlzJGg2/oQ7nD45r66nWgwWFii7qhM5MYiZQE7dbr/f3t3e2ru9vXvU6wJQtSph12YIsuk+gudJOUWYRSktC0344SB6C+jY3g1TF/sIgUDvvi3y75649a05eGvgYzXHbamy/1ePtw+/qu3R3TMrNqJuZA4l29u211ED+erPcuc6sK4lz2h6eH558+e3hz3061PpwMziFEBEJw/7p092a+9HZa5qnVaq7EYCIhY1xkqtCua/svs1PIOmDbrSFJSmbotoZ0EswCZidTbIwA19ZUW1pvKiVmZXJ3E0BorciWlJ9cXX/y/Omnz5/e3Fyb2el0WrU9zHrvx2OdJ+SM6+vd86dPP33+5OnNYT+kwpSLuAKJ3NhaB1yKlHRlU394eJiOJ3d/enNzc3Pz/Omz6+vD1f56HIechZlS5lRCwlLOHogYRN47aq3TPM/zXLWR8DAMJImTmFlrzQrFxYnZO0TU1VVNypDFs7rkREQKb2rumlMPJYiziVDUAEOVmUiYU9rGeEQ87+zuayekwd0VBIrbRCBhlrXsHXSZNh+P969fv7p99W1dTomgHbXNvQ6tL9Iq4IAQISVxlTiTokUfj5O5ElhCxymsUwlG6yiUrRTw6Kp/UjH1vJKxmNY6t/vT6WGaqXY2iLN7R7T0h6x91IeZdiV7yifzpdXT8SEf73f7a+YyHsaUUrAr04qIc2IhEXAQfqz2Ni91abX2xmNB2vok/DwUAF1jqMWGDGzfsJvRNnnGYha1Y8vvg0kDR4zFjWwhOlcYcGYP7TF3kBoxEiExjeP45MnNz372s5///BMmHI/HuizTNB2Px9vb295smkCMYShXV1dXV/vdbhjLkDMLtNfK5CmlRKiEWqt3IxJXC6GE/Tg+ffr0k2fPr66udkOJSm3OkpLkstY6iCRmOQFYWW7uYIqA3hkkDJZhGFLJvfdpmdH5TEKMJ4p6V3POIJOsIkKbWI2Z1VpLeZxsvHrrwAmJzi5QiEUExBY0/7WRF2s32zrtUskl+mXVYebsyG0+He/vH27v7948PNwxoYwJMNe+LBMf7zmlsjsg5RAgY2baYhJSVYebgXLolsRX85WyGu15/K5pf28h6YOu/bxPUtbcTw98qsurW8xH6qfkLaHnbZB4AP5b/7lMCZKIjNE7jpPf3elwla9uxiLpwHTNemrz0pMauZDZKTUcxKzXh6XWpdaFHMxsgBMZiYGU0Jybem2wDmZiZ1Zit7OoX6HUfeXSuCPCeDc4EYwdKeqE3bSbqnWzSsScSAxCSZxchZxdFxbA8eRm/B//9vN/+9mnTw5XhcfW9HSnr19OL18c39wdp8nv7ztl7AfcPM3Pnu+ePN0dDkMemMlaU0lubolZSslF+oT5dKpLtdYy9/F6f3Nz8/z5s5vrq5SYSImVyHIeyhCiZQ6Qde3oOafIK+AxHpXGcaQkg5MzSYpxDKmZjhrVVSPzTaFKiTUldHUpgynd5+MgUkjErXdwcbfetZl1dw1R7E6qTMamrC6AmJMRKzITDbQKYHGI/Eb91b0TN2IYlMgyYytRvTjNbx5O3x6X7xa9H3JSKl21TdPix8pVuR38iYxjN+TcSEh1soaWzJt0JScBJXAahp2koog+fG+2cFlqfyC4p0boBAjNQmqenbKDgbwiOWtl7AdYYik2Wu1tWRZVzaC1wWTV1dgGa22649vu4SysQF2WaTrKMIxjub65Wo6nY9O+NKgak/KaFEepr/YWnXMOkDCiD3DVKu3N1FZFiceE+rwvzSyAczDcYG7Bkyd+fFjQfd0Ac6FkbrRy+KPDyM18yEgZWfD05ubTn33y9OlTZn54eHjx4tU333zz7XcvXt++Oc3zPJsZDiN/8vzq6dMnz549u7k+HMZhKMzuyJ0BitZvVaJVcVhVwXQ4HA6Hw9OnT29uboatUzuuYc65lCwi0WOoqt36CkEamStzKgUQ3kVNlYWYSZLCR4O7926tLb13qJn2c95mrkHxDfx+00izcyPp+iHRREQ2Md/zpd5U8EOqm0OOG6DojnJ0kfD2SlvDu7beWnu4vXt4eFiWxY2C9xuG5D7PS6sW5EbJZk6iuvYyqFM3NqArGZKDht2BOYVO1Xaur5OZzxIw7o5odwLO1LELY34LS/2IuZs5ofc+1yUDROLWfVswRxT/14yKyN26IkloIU3TMZ9OZX81DLsnT56006zT/HCaDN68ixMJa9emWqN62mrQ/yMiU7PW+rxUrW3rp1uPJDqDq2HHIApKjFnQ4mNSVtSdo4JkKxE1Gv9gBteYPEGhvR9tLEIYShqGoUha5nl6uD8ep1ffvfjmxcvbN/dLWxGtqyv6l5/9/F//9enTp08/efZkPw45ceFo97CSMrn22pZlcVUzCyNzS4fdPmw952wbBYCIEnPKPAyDCKmumqBN2ziOzNJ7c1uV5kkkQnBwckJXc1Nlg3MMb1BVa2813ap6Nw9prlLKNgEt+F094HxISiG9ltb2i/AjRMRJgksHOEjjqPGoQXmHmcFACpwnaa67xd2ZpeTx6uqmZOl1rnWpc3N3c+K0DGNLtSlVSnlVe4BE+dYhaqYOB0Wju6TLIVxn+3Z4DAh4Zy5gtK1uNGDyoHN/r3ffqFeqmp2IqHdNZr6qWT9GWmv7D7P1TqCUCqnXNi2no/XG47gfh6vr/cPtmErutXaguQUopq5dda71tMxLaz2BCd2tmS+11lq1QwicCRYbYSU0u6/s/nX4Z3wj34RANv1lB5nHZF6h0ER2h5FAmJ1txSaEUBJurg9Pb/ZX+12t8+n+zcPDw+n+4fb2/v6+zRXMGAfsDvvrpzf/+q//+unPDs+ePHn69GYsA5MnRiEWRpYE68uyBOvd3fMwjPt9kXEcx8NuPwwDEfXaiK13F3LA2EPdIMUl7b3X1lU95zjW1hkBTNy7gQWualbVaq1LDcHu1nvXXs3MewuLNydfZxBE9UqY2TdwA0yAMUNSTqActSlyEolCpln4ivgEDb5aGHx1sCsrhEGkHHwbsBBlERr2ZOzuKaW6DPd3b6bT0roPw5DKuN/f7PY3Oe2IknYQwS3G27M7iIUJamBJMQBn9XQfUAhbTxv4OcQ4u0YPGZzNu291gw8ZfgpqWHTLmZnGbBUwkQlnAQWm21XN1FxFuHtoAzibede6HJf5Ydzvc6E85lSEM3vi3k0YbtrN1G1udVrmuS5Ne2cSuJr1rktvTUEOYhLOnN89kuKY2f5EWISuJVSsVWdbyfnx4ZkgJE7GUUAlhRoTRHg32LPrq+fPbm6uDnA9nu7vb9883B2nyWAYMihhtxufPn3y9OnTm5ur68O42w2llFyE3ISIV9VOcZW9yG63U1Xrut/vnz59ys5Rf05JmDknlup9oRB3Vm2qJZCfoMTNtS6tcUrmZE5s3B1kQcnqTqzw0Jx6mE7LsszzDO20TgDwvtRaa1DrJA9ciq09LWEKkc2HYKDkLEkkDSWXlKiH7tI5YfUV1WqwFS9aRzGYBzddomDtauYhFZg4D4cnQ96XMuphqfMEo2VWcBnH8fr6yfNPPrl58lTy0NTm2lU1MY/DnnMhTiJZDbU7ccrjLuec1hmAYe6BP2y1FxAjExkh29sMgkdbJ8M23enD3p2INOShmLtbU12HCFEYDW8hTFyOlFk6m5u7Njixm/U2HR8OV1d5OJSShiGnIjOTrgO3YOzVdGrL1Gr3viYU5p2waSeBGMyJhAuvo31tnbC7fvYITshgBCfns1rvRWAXxIrQxhFiB9LagKvuUf+X6125uRqfHA5Xu0KuLZcl55Yk7VmdmJMTdleHw34ch5wopmP33ha4khu5V+GFpSQW4ixJMolIoyY5iQj6amrMSEwGT4xOhu1/30igkVWboTUV6QBIWB2tqzvV3mprNUbrwJfWTqd5mqbT6QG0jkwjoNa5L1VVnaWYJ/faXFVZKCVubaNQE0nOw5CFNacicXUAc5ecUsnM7DB4h3awRboB9ZgWCzKYeea0oiJETMxJBMhXpVhORVub0/TwMI+7uhuvdoerJ0+ePH/+s8PNNZEstXU9tjqZcU67YXdgyZyLqy9dWTJJEslEFOYQlzAyDjdzEyeQRPcquwN0afFYbd0/GrWv5o7EgJWSd1d705O3yZnAHCSt7tsuBwdPLjpjurmrMXFhMq3L8f50v3+S837Mh5vd8WG8v79vSys0iLB2Py3z/fE41VMkqU5ea+3M3RxMnDxBiGN67lZa2xbI3R5jMtomVhE5hwJJMGscesEcillCTs7QKN4dRrm62v/bz2/+5dPnNzdX+7HAjK1nof049qaqDk5ENOzGPA7MINi8nLTXZT4xs6uZWXTuMmhIOWadMkgSFUkiMqzjVNFNDWSurS6t1WDtxj+dy9ohHTVNy1J7ZJkKtNa6+v3xYVqW07xEObSr1lqXZaltNusMipFTG20URGRO3LV2bRqt+0NrvTV3VxHKpZQxkzWPnl2Y1hbV2VJKSsndTTW6HeMWqLVWW2uLmbp7yjyGJJpkoijoAg0wzJPV1urUl8WZx6vD4cnTp9fXTw7XN5R3YBGf4XU63WttebiSTJl5wx+JkEQG3rRU416bwi16RsiUiDOiq9HFTcGhVbiZhQOrJsDq+z5i7gIIyq7srw51ue8La0NTY3LzUNjybbwgB4udiMiNTUnIEylc62k63l3dHNJwOBx2u8OOEnXyhg5wbe04ne6PD6d57qbm3rtXVw16DVhEEpJQ4q0Osho6X4RoDDKQrMGbu0exyGlzVFgnRoWqQe+NyYUh5M4oGddX+fnT/adPr589OezHQRL1pQpjNxYhbk1b6yw5DSXnbO4GI9jD3cM5M1NVbatC6pDzWIbMbGY5cdB6mXmX05AlpcS09mJ7b+5KtJYSS0pndMHda9PWj+4OkZwGdVuWpmZv7h+O0+nu4bQsi7q5e4uBxl5VFa6JacgppVSyRHTkK83a1HpK0QXCtRrIWBDDArSrmTVrTm6tp1IB3kg7q+RdRDfk5GqtLfM8W28pJXKubh4FWgi8qyo7eu+nqS5zbU3V82588vz5z3ZXV7v9nngHZyhbl7rg+NBaW54sMGVYBg1gY+KUhuiYu3TWMHYFkURbS4DyiEw3urffqqVuf74f9l+au9uSh0Rjvn56fXt8pafkqtVqaz2DM4swkYmZmam4J8mwqOs7w8TJ4GwQ73V6SDmPQ97vx5unT9woMTv0OE9Lq1OdlmVRuJnrSnqJIVckxgYTMqIUl5uFQebWPDYbkXUP5CBGHfLaIhltSjFAfpvaE9VctyxgIDHGEYdd/vTp1Sef3PzsZ0+u92MpqdW51ZNZhTdhNwaVzCxJWNaJf97mebZTxLSq2vsjrpcljbkMw1CyJOJ5ruNpKqWMjFxkzCUnSUxBRCxZhiHnlIg8PGVEa6EbfHd3p0DJI7iZU6314TQfp+lhOh1Pc7DElmVp1ohItWaRlLjkNbHrvPbBsKqpKXnvvdZK7GaWc6iFS85ZVVNK3aqZt77kJO7oqimlWhd3ZUbrqt5hFGZfSknE5iFy79a9We1VCXXtJPIYxWxdSY1vrj8Zx3Ecx8PhCTMDKaLPmADClMM9C4/MBZ1ir/WmeTcCrH1VTMDamCLuXkoiCFNyA5xai5z3bVXI86n+A8EMLGWSfdHr3Xy113lU6w5yhbsZ0chZmMg6GWObuUMOoXgTi4utbdZWXTszdrvd9fXVsix1aqfpdJoepulYa9WV5bNuQTI4OdTNVz9tZLrm4IF7ypaQGgdnN+TEGElYIoUxMrLoLLe1RAAhp4ycIIwh43qXb653z54dnj/d7TITam+ttwXehd2E3TVFmy4c5K5dLdIhm+aTdqu9taattVa1abfuzDwOeRzHXclZ0pCllFJSvh5TKUV3w24cPElJ7JQc0b216SDQVqPp/Xg8vrm/b62lPJiLqs+1PRynu+PpNE+naeq9V+2tGQASpARLICLPHIotcfaZtWbqwft3JXLmVRPsQlwQ6ma9kzb0xhuvibd11g0mImZh5szSpZtrrwsRETtBYOQOU8T1J0jJY05DNEWM4zgMO04JcQcDghEbxqvdvpXeS9mDhCBnuCE0WUO5wx5nfHsgziGwTHQ+E5O7kuAt8kkEAA6Q4uMrmTcm5THtr8f27Bp6qtTbUWtvqp7NiG0QESRHj2aA9RqRw03gFjlOPfV516aBy263H66vr6dpXuY3S53mZana40KArC6LqLZAFQ3BWDVYnBNKSlFQPkdlEaURZB2AAWYeghmiys18I68TkAkpeVCPhowk2A385GZ8cnN4dj1eHZKwau+tL8uyeG9xRclNUjI1J6aYlBqNwEQ5Z4rDgx0kBmvVY3zfvLRdtaXksaQl5SE3EalHDEPuV3vTgw0FJbmrs4g0VVFrrTEk9V5rb7XWudXT6XQ8zcxTV1+azUt7mObjaZ5rnWsPJhwAESSwCEuSVIZhGIaScxZJLIS51QBELaB09hAqU/V1pnjoSTVrtUMX9EZE0bxtG4IOgqwTCyWGC4FFsrj1Lls25XAjVe+kZk4kMQYH6xNTLgV5CJUAbGoUKZfD4cod2vo47EJjErTeZuZQ+2AixyZnqVEJNqPLyezEW6v+O16cN4jmB8y9EpwYsh+unt8I1SnTVARMNte6NNcGIBMJmGjV2AxklGDkRm5sjF7rdC85X5VhyGkccrSirZHuMDx58oT3w4PWdn8/z6ccnXg98uBQ/PQQJI1lvML97g4muG1Z7Dohggiqxg53yCqxjpQRddOSaBxkyLwb05Pr3c3VOI5MWEu4tS3LPJt1Igmyq1Da6GbuRCHZxMzsg7Iyp5Q9FxVeuh1rn9UNDarzMtclpZIlBivU7OM4uirMbT9Yz2PJVhILSZNUW2zfs+JNa+10Or15c2dOS/Ol6tz6aVpqx9LQ4yhLkII8lJzzfj+UIe2HMg5lyCJs5KG3wHRhPYmSk6aUzCoA30YPQnut1Vsjq1nWRgozq9pV25m8tAEC0R+9qkoRbXiIgYVEEvTMWA6ttVXqDdEw7JF3OjGz8DgOzNRbyyVmSvpWCjcRAtYGtvPv43+zSswOck++Kq0wCBZmvZZjzgH7D/StpixwVZAic7nZ5fTJMOYy5lTyfPsw353a0qg3J8lEAlJzXvmZDgNc2c3Jvbc6T1JmJnDZuhKJmbmU8jTJcNjv61ymh2PvR+tmFlPcCKHCGrIY3h1GiOQ48taI0iNzJWJBBDZG5mZdIOHYY1D6rmAYUTJd7ct+N4xD2g/l+uZw2I1ZmNmsd5AJW05ozR2dJYkkZjBSGLkTMhCy9CSi3UeHg1u3h93kkolP9/f32rTNWNwmrkNCScQCzViW5l3Jze3gmhk7YkBDT66RsHhaGzsyi4ia1Vpbx7S046K1rYauW9lEskRvYRnS4bBPicch58REpt0dRt1ikCCbGZxTAktTXUdcCZmt1AMz67WitygeEq0U3OBxqKp6ZwgkAsfetZMpscfcWISVChOTEJAYAHgFy9ZUkYIjbO4h1LYaaSJhKZYzMbMAKTr+HezApnEFj0/kcEnOEqIwCH0vf0QfbVMOWydVbLXVH1gJpKAOONgxZEr7Mce8dRLO7tRxsqU3UygpEXuIqIY8r4ZEDcFc2XqzusAcicec9vtdGdI4jqpKSQ7kwzL1W9qfjrve+rIEKB9SCUFDgqK6R+IVyAtzjFBcGZLMgAgB5t1VzSHmsk37KxnjgP3IpfDTJ/urw7Ab8m4crq8P+7HERbPZAfIyliK95wiOiLIbmpKGjGXAtwyY9RpQhjtYjVpV7aTdmbISFOqKOH6YPYEaHFZn4amknKQk9J4HXHASgYiRIqUb97tSCicxVXXXrVuIExwc3z0PKZVBcmLJ6kbOS1PVRnBYjTN2f9gF94aEnZiTNPWYvxAk6tZaKIppb1BLgBM4SUqJ2FVbrbW15qo5P4peuCuRblbWsHIqGc5gwaVCVWxNXou45gZaVQ9XUxZnJk6r8g8k5F2czSIRXCvhEUIlSLIhY3FjEIsTKZGsOT53MN7mFMiPUhGrdXJVgol3gYIJJct+3NtNkpJE2jDqw6TH2Ws1tY057VgZWyG5xCGK0Oq8nB4GpGEYPnmaXr16XecjEVGSBba4nrsTonRl5q4wtyjCuLr6ym0LIqoRgv0hKQHGYGYOLQgYNlEkTllTwm7kw2HcH9Iw0LOn+6vdbhglS7ral90wIqJCWqfDDWMCYIrau3aalt41CvWm3t0dAmZ2LbXr0lQd5rw0nedaVaelIeaIZOSEkmTMJQmNoomJczkTdIki417N3d2JXFIqpYzjWMq0TTULqNc4p0RZUgkRSTWDI0qnzHOaOGXJwonBZIkhbCJUtIhZUG6k5JRLd1uWpda6tKrWltqnZSaHdQ3peiJKqQQEWWs9nU7H4z14p9qGYWBm66rWBc4SXEJbRcUi7IMEKwAm7q4OOHNS9x77IUYpMwBdtTgBEJggQeVhZnU3KHUCoHgclh0q6q03RweBSFkKr0yHHufAYxef47El6vvN/Xg8MiBsAmW3IVM4q+HqMMiwk9zyWOV+gTTAW/etauih3EUr0C0gA9Vaj/cPxGPZP91f7692++MwVO3O1HsLgOwsnxsYY/A1AnLZzAFRMnbGeVQ7M7uHs2Ns6TqHSjp5ljSMfLgarq6H66syDny4Gq/2JQklopRkk+Yy1ZhsqNEQ5Ea+LNpra3VZagB/3RQIuJPnk8+1TUtrCgepS1dr6hRsgiK7nIacxyEPSURkRwvDh7GsiSTndwhVgTxsMIjsdrv9fr/f70kUlLgYSyEZUh66ofZW61xrVWu1VndXrZKoJCmJk6AkHgrnLLXWaMEmopUl5hZkY3dfBfJqo/OkrXV3rVOiaq1B9Fe/jWbzlBLMQZ7YRMgHITeQcQy1wCZ6CXfA3HoP0Z/ulNydOYVCEK2S+X0zZU4pRfNDoG0GjRwvZjTEhdK6jkjIBcRAMmYwsbO6s7mCznp6sewHIPcwd77/fNXZVY+5IFlSShkkGFPKV2mXsE9tL/UV3d/flzoVluRCnVELdxNQUiZJcM4s08s3++EGO4dwPhy4DPX+vhndL/1u0m/fzNXKPM+95bZYb6oKYjQoEZAw29ptJAkikOTMoSBCZlwBdmVoShCHEEpZsqBk7Ea6vrKnT+j6IEOm64MA6uZEAu1R6HFv5nPXFgRfIlHDPM/LUh9O8zzX6bQ0tbVRGOJEdbmZjvbw0KYKd2fupWCXJQnvdrsszPBhSIdxzFlySowuIomJE+UskoK6rQOvordumtwMZqQQePVBytW4d33AgGFkiA1DJzFVnablvk3em82wCmtoBGW31DEg7ZElF5ZEpEudiXZAIyllyFLQVDwbpHfUpakaNQ6V9+Yqw26R5608m2nP6Zot27HefvnNMrwuKZWSx5xCYYqESagycs55KCTiBAPryuLI57TbzHqwr3yd6hN+2t2j3V5VaSjWtfeu1mmdUmoA1MngwXJrDnOCMFO6TijXT5iK0+zJLXGtiFZyIJODHbTq6Sm4fXAy9qO5az/5dhJw6I4jAzXlDEsAI9vuquT0ZCiyuy4PXy1mVJuyIREo5SQps8y1kaFpW7ovcx1VUWg3jOM4ishxno/H4/F4DDJ0eJQtkAUHMwfmjpLI3ZlgBia4usFCb3QFh0HwBjImF5axeM6y3+XDPj+5GW+ux8NQYvrdKisYLb61kUBVsSlbbGWjUNtbSVRlSNLdNhYDU5Jkh6uy2yd36v7omHOWXRmIHWa7IY9jGYecc04kcfoUwXnSeSKGGhUKDVRyuJmARORqv7u+PtTenYATGVkqeTzsUs7uXmu7vmrTsdZF+2Lardrk7sSemXOhkiSxCHGJwlZKzORq0U84lHI4HOrST8dlWdqyQIFSNKVVwzWldHV1dXV1JSxNO6uQ59Zqb/MMH4THkgN0EuI8lNG65AJmEoawg3tbNsXCRzU4AMECAR4HC6//dISrda2qStHcxG5mx2myaMImUYc6pZLHcYdnz9fbjlWDZBuH9cO+/APmDrv1OJfB7jCYYzbPq3oz8f+fuz9vjuS68kTBs93r7hEBIJFJMrlI6prqfmM23/8zjD1rs3lj3dOvX9faJakkcc0NQES433uW+eO4B8DkIlJiVY+NG40GIGPxCD9+71l+C5LAjmSQq/EwnZhaa/PSjoude4SjY344IDaEbtG9n87HaVnqeJh2w9XVvr4d7fSwLMtpPrfWunZEzq3KfdVcIEwxHc+BE2Dw5ke7lo7oUoqwQKyysIypWhG18jSNV9fjzdV0tR+FAxIRm3A/xxyPo4e7Fy7MUEoxi947YUdEkVLLqOGq3hZdUobYnQhfvrwSkVpHEt5k/QIRh6EQ4NLOuiyl8m6s0zRM44i+s67aZlg54Suo093Tl5M2Zh0BFeJpN15fHdwtQAEtAMquXl9fD7vEkJD2aM1tCe3hDtrP7tZ7D1s8NJvm6SjPtZRaMM3dtRGX3VD3u6u7d0d37x16BwMQAWZO089hGG5vb29fvHBVQhnHnVXuy6ytmSkwoRcwcaFhGBDS/Ny3KSEG2soeywXezM3SOthXnl6iVc3NtHdVFW2ADq17b8xcq2Bi308P5haAQdy6qcO4mxBuzG6eJvSqHpaWrn8JXVWYzwSYujuAgKkZRk0BKS1BURAFRABdmG4/ebmczw9vH+Z3Rz0uS3NVw9AiAzKDKRDM83w83tf9YShld9hPuwFeg1rLXtg8z4tBa+pq7mvNhHhJKYGYCmOuU6mMl4ggBAjP/qOTIxUpzEKWYotjqZlxIqiDptogESGvWoNEZIglma2CBjgMwzi4qlrCRYIi0CC0r+N9ZpZhEhGuqyRL9vIQ0awz4NKkL4WZx6EMwzCWqg264BLq1oVSA8jdVwIrRuDaeQsMYKTCWqvspqHr5K4gMOyG6+udpDIHSwSaorVwp3AE7araddG2qC1mfVOKFGYuQwUWDyQkZiSshTtiFlmQaKI0Jqm1jtM07XaHw+Hm2bWpI/IwDCR4FjijWzOmYHRGw3ACkWSoCAFuqbs7owFagCIGoAF12ti3IgkYRtXo3dIcZfIGAJ26kAr7vhZm7t1xR8tiXdXDGay5V8MxRrO4zFkjVnAB07cc6H9OuMOSxANMoLAHAgUIEgNFyloDOIEhIxCVD67LPFEdpAwnOS535+ZLdLcwdjICIpn7fDze786HYdwNQymDWOjc5vP53HrPcDcztyzviYg3c0woDERYmAZhoiSlbdxMj1BV76HGhLKqXmPelKuNNQEBp4ckASbjOA8iEgReq3kqiCTFytog6r0nrRtxVfZCYWaOFTKVyi1gwqrh7uia8iwx7qskUTqEPYzA0QUcKfXbERHBEdHVrCuhBDsFBgQ7MULhGApOQ40Yg7COdSgklbZpGhnmdgUASCoRSYYqboO7eqiFuXsglaESFw1AEiBWNyIh4KR3IUKmWKWUWuv+MF1d74ep1jFLaiKi8AVBrR+XeSaM6GIJ+gyTQoMXcEFhQAIETsZKRFBctpqVuiVSCoowAKjCQpbGkYQKAIzmaJWwCpRCQgw+khu4pbURMxREcUPEcHT3vOCFyGLNxAC+47wX9GcgYoKKgSm8zqmzigDgacyUJhoYgBCCQhwwDlBlYkIueT1nJj0vi5l4aHgVaW05ne+Px30pjIKlsGo7n8/zPK+ivh4AwEyZvzImWAWJCF0xAsEDPQh57QMgBHqYu0M3iGBCwkhJHmKUVcUjiIgRAhwDiLgQ8/YfETm6YLELDoJISCJCPaZp6r2rpoFjHkJEkXodeeTEEL17J1ibwJggHjJBlvTHY/LKYViZGYIes7UwM9bAguzgyEye0uFCPBQ2T0sU174wuWLkOeZkAkEQnQkjgnMYxxQhHmDBOXumOiCxABIXA8S2kmgBwAwigBlK5uJMwzCMY6VCKMjCqTADzTC6alvaCcKiVHNmpFrFrBuYoANw8qEBIP3SGSKtLzdtmBgGLqWUKgCgioCmhubgyhHhSMDixMGCUoSqGFJ37ACpjcpR68hckNKx+VsjpHgfLfOTV3dZ0WVAqy8iGa72QBoBbp4fIMIxCKJiBw6YsMJAglnDt9Nyvnuwrr1pZTfo5/nu4VjHSXqggS29HefjuZ23WIptcpQrR3LvAgHQIel2aJErMUUYIHGq4VH6MQlzIqAYMVU0ViGJAEKP5B9svd4UVAEATr6f54ybCFbxiUqwzEvvvVnWQU82BNmlLUpYpJwVAwNISita6xGGDgIDD1JlILAoJAxhRqukPUhKQgJhbMZGAAyIXDv0ImxSOvdBxCAsFLQ/tLO7pz47gmBQOCEya+oCxNqOSAl78DrtkAiFHQkBWYpQZhQkQkxJ002zBpHCUoA5HF21nZdT15XcJOBBwEIitHbYmRChW+tu6oa950wfCM0McYN5MBAhEKYdBhfmwiACYARIkuwl0SLubsDO7lJUpiIDcyEorIKdrZuDkxSsE5QxF54nnVzaJDVW4PdPMdx7DPf1OZsaXQRigFPgytuFlQaJ1MHBoS/vwAGDhqEOMg5jqQO30zmwn44arlDCz73pcprfzcv0EDLrMvd56XO3HlgiIiVEtmBHcFezXPMHAkaoTEXWBrtq9uKNhTBVxyCFYoBSzIpZRCqLrBij/BIiVvLl9hcAjIsp8lrapwoIAOymaWHGZVFV7U0XBwAiWdoJtvYCreAkMFPtPW9YkTLIUGUoXAsPVRzQTdi6UoCbgUcpJe9MvoDJPdfdGLAOUqGuJtcM3j0QSb2DqXcHEkR1I0s7OjOItIuCUrlIyShlWbUxw7ItDsKibgCxmpQwIEIdeCjCjONYUdCsn5fT/f07DxSpIpV9OZ2OD+dT6wsFWJC6IWKLoHnh08wlSJTLQETmQKS+ms4mpMwQBDEsCCPEE6nv3ULd1b3L3tWUBDCApeDEPNZaXQXG4g2bng1CojIMPSoFIjICI1LKFwMQP3HM3i44/aSpKoIDEkJAGEBQurtgeBgBBppnzwQaAgNYCw0HARYCLgPUMpZpPHNgkzuoe+5zM+5u5qDNTqfGd8e7s87neV60z31OLVtKpQA3B4IwNwUHZioI+13djZNAmPVQ69EXDQQgDGJxJgBnAkZA8JXDIUScuhQayXCkAqtScJo8OK5aLsDE7g4BQtsSXqu7l1KKyOl0SshORLh16+s2ukYqIGAwS1mNuGiQshvH/X6fXGzipDxRRzidThgwDlPNYCSKwLTAJERGAgSJshv32r1y9QrqnZ0smnPBAAdn5kB0S/1jB+jExEy1cCnChUQEmJDYs5lLiYP1QCeiKkDgxCEEDrCbKmKUioB+fXMlVSz8eJqBJRY1uy8Umi2FpN5QMWIAMI3aTdQLByswBqWvr4ZIQUwF1iCSxDgFQtNYtOeqrIGOJcg7FigFyMyMWFQGo3E2NJ4aqPFEg1jviwYYClUi8svwNNb4jA1E/m0p4MfjUsi+168UgIDEDjgCGIS7G2CuBp72xKm9nfBiohUY1twIXbBADSC8wb1MUe/59HDu0GkxR70/3d91fnN/dzwfmzXVtqg3Qw9K9iM6BliYg0NhGIZyM8DVYX91OAiEtjbP8xkAogFiYl8dPQKJIRVOc7MrdFHVSmYfuzsCIHDqaEJqmweRPDpcIyIRi0hhQcGIEGIhTtHg7CXf3hwAgBg3XbOgAMhEdWvDr06RzBHh4eqRG0KYp/62SE10LazT6NiuBxXizrXKoGwpeJvquiJi0gEDWQBIi5sFIoads2VUqpTCpRQRQuGlqUYSb9wdwQyQHQwpiJ3CWUAYxrFyWYVoxmHa7fbTNHEtHpwwfiZxxhAg8lI4Q9ndWSRk6s7WkRlyVg0BInuDnIKHiJAwAJh1CAiwCM6epAEBA1dBKxlhgWTIanzujogMDFSQjQQZBNmplMDim63FKnYUBBtV+zvH4wJ/qWXfX92DdDPFRABKX0SHzMGIsBCGIwL0FCvzEAz3CIZqEQyCTIAEV7yv+2EqMrJzLKfem9+d7j5/t/zhT//69dtvmi3dvHewCHMzX1GiafwnBNNYd7vpxfVwc9hfX11xxPn4cAwH7WhqKfdZkKgE5ijOI5AZRKiUso7x4lGohFA4+eWes6q1wcGUNEQeypBY7VTBReTKtXJd6ur3oqoQTkQsaXmTmCTPvjsD46ZOykwRbm4EwKscHgkxIuetmFB0d0cIDaibYFBEGhUVIiFQCiOUYAKKkILpowFkJSyQiBlHRGQh5qw4kZmDMPCMFj0l+8Aj2D1FlzxhuMwwjjSOIwlKKYfD4dnz249efvLyk88OV7cW4MHuvjvs81ZH8FprYYoIVw3HWiuVmgHHUlMGHVcCxtqNEeGIQFczQ1zJ9RiG7lzD3YdpHblg4MojiQQhwzQhc+l9nfqldmApBWm1OXBPqdKVBfIE97vuJ0+smt5f19dwT2/xNcENAwIMTGnpQGDqARrE4ZjLpGqDIAFG6GGmSAScWjkwFhnGPZMhYmnL67t3x4c/fv7V7z//19dv3izmyEACZOnmBLhBR4lgqHy9311dXX14u7vaH/bTCNqhzQ2xAhgCIQiGMEvloHBXD4+ATQtXEjyz8baZiRgF1zI7v3QmlnBAJmZKTCKtttecfRhmZipMXUk7dSUF8dw9AMPV3DU7ggSa5mGlCG9cE8DQFgRYpdAAGBQRSWROspU7ONg6r7IgyaU4SUTciMh4Ba8LACaAmhyCOakXUmqmTLiJS65aA6UUB7MAoVBfIUngptojPCI3zyEX4CLDUPdXh9sXL15++NFnh+vngIKU8ve4daFcRAphThsIcv9kgHVctjKGcY2/LciyjPRt+Lme5LrdRbjmiGPtzasqbeVTOPo2oM3l2Q1wGNOfJ12aCZGZt4h+f/0O/MF1fR0FEJfwBK9HLrTrzCyM0MMZCdEDMheIKF4ADCEQLRwVIMVrK1diABzKbrgCBpxfvX736t3dn7768uu3r+/OjQWpAAcAo7dY4dMOBCAMh914++z65ub6g+vDOA2jsDbQImchxkBwAWSCWrAOBRnMUBUu/ie8EtQcEl5DGMgOkXsAhmNw2pdlurIqmq96/oCIRUpGvLsXEdPQoqrquJakEG5IoYlew2EoeafRJi+aLV+OtEtn4wpAYGmQtCb+iXZ2925KbuIoxFTWua+t5BamEswEvJL9I9AhMtxZlIhY0tTSPVTN0F2Icxpk5EIckWnpCppAhFKw1hqBCDwM09Xh9vb2w9vnH98+eznurz04UBDZRWC16QOkYMBVmi0TrSAAAkpFvhwPr11dTJRkRnQEi8OWaq4zqYtOUDJ0EME9egcAJAazldxk672xeqoB5TYCEBv5/scaMZd/ffqwyz0gQANChDlmeysAwlfhRQdAR2cDgyx+AFensLCw9SXStlABohmhFRplGvBkp9Zfvbv75s03c2vJC0AmEUpu6USlNW1zd4NScD9Nz2+fPX/+7FCyx4LiqkPZ1bIIK5MTFeGpSB0qMjQFwK76rT0LgYJW4bTc7MINPBjSiokQMdOey7OYSyJvRSoREUpEOHuUtNgOB0VEyG6Srw7GSJG9xVxRstVDxAUkfSnAHD0qV0dHJDdIjVGGQOQAyhUUIBGdeBnZGkRaQFDyTWSV5vSsA4kRggmFshMLHlzytVIMqxsCAXr3MHUwL6VMwzQMVMuulEG710EO+5sXH3784vnHz559MO2eQdmxkQd54GqjhQBgETk1AILgwiv8yAGBcbXcIIzFe1c1CaFaAR2dVLtI3b5jBNsGQoR9PiFu8A5Hc44IcWQZE08CFQGczBDmcABL7Ut8vME8AuLpdY/vpC3v3RKXX8W9QKSEmaFv9JB1KpnuJmsLL2ObVoxMBFBARIJdkNW7qSKEIc3n5auvX33x5dffvH699DaMFakrsLlQ5XAag4XK6Xh26xFQa9kfpuvrw+31zT5Rpu7Mcph2cKMIMQyDE/JYh/1u3E2OcZqPEfMFh2SPeisZ1jkCCnAkJCYULk+EQtdSNZdzIsqWc4J1aaP8pvxC8+ru7j15NkKAFIyrI+Ql4gESwGxoS+gFXLPWrKrOXJK5jLTixog5vZUQGdnMhvSwXrSDR1BIZjkiiBhISYVGYE6NOU41dMk2vEMQqbAXM2JvaopJm4xxHKdhV+oIRL11RLq6uvngg4+uDs+Yxt6D3XtgCjAgC6baAwSu2MFwdNDMjiQljaLHOswgDvdwMEXMBzsSVkQBCnBvS0vTVhESEZQpB1EegYzMudfZeVEAKEy1ViQx0A5mEABLJmbpl7i1l78V7jmJfC+4v79UNSVcR6oIjJCgAUzhBccIg3QsjtUMvGlkrkaOlPirVONlRCKk1vurb+5/+69/+P0f//T1qzfIdDgcmtnS3FyACmEhHtrcTd2WZtjHcdyN034chqGMgG7dtZOIwEgIzLzbLwZAtYyHnYy1ew9UtQEgemSopX7lOtYDACJOPUImqkVqqatk6cYnumRBiJijzYRcQuRWsOK6EIpZ18aGndLqmokJzCy92XKj7KraW+8eOieuJtXbIlbD4SCGoJwSJEIrJ/kiQETopFVLZW5MTu6ZCYiI1GRaAJqGmdGqSLEqNFGAE0SEMCX+g9wDndkbKSJWXVWTRKo6ZOk1jruXLz959ux5kcEUzB2oSh1QancFj4AEtEUgprpOmCFQERGua461fk3KLMzi7smWEpF0mQV37X4+Lcfj0cyGYRjHcff8JvfegCAkJg7Q3v14bgheSgkuhcgCHNCJKq6XzA3oonr5w8ePpzqy6G3ukU5BoQgKYGgGGGsfAVceSwcEgLaq1gFGEG4rIZIZmVI4LrO/vT998+btw/ksYx35UGut6oN5W+zq5lak9m7nh1NvJy2AxNcDP99PV7VeS7kpvixw6l0K824UK/VmPC8zMgRhHYYgBBqc1MEUgvtZorN1saGSIIYACbFZ4tZDKvNQsVasI4qIe+4GzinvGYRMJW0XCJgxbb4iMIgA3BdXZwhaOzosyWzclH4AwLyDqdq8tLl366lynL4x4erq5O6duSSwp5RhrNMok0CJYQBm1s4GUjuXBXUJDSCmqBXGkScSASBlMzPHlr11ZmHOUXE6nQCAQtdwGyhclQiE8arDvchuGJuHB58XCLq6fvbrD5//bx8+/49qON/7w/Lmg48/CVAEqFHVwgxKFUJIjvmyLKfTCQCur58hEhfW5kBoFoULMZvqsiz39zOgM/MHL69Tl+N8OmvH87m9efMmIn79618P4/2wn8CaWedSIFA8Hk73d2/emcO42zMNTEMEo6MAN1OCSKdlWrMMt3BYp7ePDZm1cN3mr99bswrgAJgTsYBQNwXoxOGugO6ZKiHEpjS53tgZ7xgbRwc8yAFbj4fT0jTG3fUHH3087q6vS+3d7u7v2eBwPX726a9F6vnUvvz889PdyeYGapln5LKX9Y0Il6GWwhEx4FAGAUINK0N1AGQ6L0Prw6yLeru0BS5Ljqe+88WmgghxxQskE5kiYEugg5zCIRhS+hk3pZKVrkOEnIVuNtpyEqzpQ20pt6TL0pemvduyLNlD4IiQZLWFBzITMEGyJYiAMBhT5B4AIHcWWWvu2Poh3VRUCzMyUtYfUIAcV/WYbbqIhIRpPJ1iQAiOuII1CDkHEckjY8ZhGK6fXdVxWI7nh+P93ek8XR1IsBZ2BySnTGtXmE+f59Pduzeqmjskg4hgBDh5gAGih57Od2/eflOl7HY7sCVXWqRgAURQ7cuyvH37ZphsGIq7ZoUFBvPSsu2Lqy1UbA2fp/oCf552/VMOkXpLBMSI4OEK1CPMYRUsybFNdjgjwoF4a7KuIIPQlAVzDEdWa/OyeJRntx8Mw82ytFe9v31793A8M8TN9e1nn/16GKb7uwc0nx9mm5svc85ohJCFEIgLl6jDUIZhCApm7DaqazMl4UAk4V1bFu2T9lOfH5mvEQRgCBiRvLTMfS9SQWsZhpheUymCmR4h7o6MmG0XWjFJiMgwABiRUToFEKezOWgiCdRVW+vL0pel927aMrzBHWGVoGMSIC7EBZmCKYSCKZiMkRPvD4jCIpL8a6Ru2b1ZFiByQgkgImRiKIBr8cCAkfdmAEDmYc4QisDABOxAEIpYEFm1LUs3iHEcD4f9zc0VFuo63929vTud988O426oU/WYCZHYVr0m7L2dH+7fvnr11fF43O9345CDLQE1AiM0CA9fjg/vvvn6i/1+qsOHbg0RAV1KSJFxEilw/3B68/br3WTTwIWFCAFR+9zOZ1UVoVJXMhBcUKiXgWoG/cXIIOAvuwGk7D5Kyz+CiLCAHm4ATpgC0ps1a1yU1G0VtKfMblVVnQFStVqaDLy7msYdXlv0bvV8Iq7H07l73N7efvDBB7vd4Xp/BWqnd/f94WFGqMK84hNz1F5yjlPGQgQkTNpiCfSOGCRUqoxjHZYyDMWGgUWIKGWDLAKAlBJXTJlWBqEjGAS4KzMTAwEw+zq/CI9km2MS6ZHlsrogMGGOk7MFbtFN1ea5qaqlak1rrfXW3QwIJd2BM8FwdE5JKGFkBuEQcUIjMHLKQWsWu4TITEVW9zz3bhGtOYAFlGKlFBIuUhO8sO2ya42ORABEwVu/jyAEwCI4HCHILcyslHJ1PV3f7EolgN77eWmnrss8n7ouZmMEIEsKTEDqZfXjw/HN/cPr16/fvPz4xf4wiGCVQ0APSGPQUDuf53f3D6+Ir82v1M7MjIDMUAa50vH6OD0c38zL/bu3sd8Nh6tdAUGNZZnneSbim5ubOuyHYcrFC1fFn4Ck5sH3ab7/BeEuwwcBHmGBQbwOOSM0NaBWoYV1CJVPSftPXEnp7sHK7khOFhN0Lnp4FqbR5rYsXY93hqxOqn64vtrtr672V7thsq7vvnn98PYdtI6IySWpOSpCZ2KuXEoBCmLUAMe0UgUBZEEWLIVL4VwPctCjsZI/hFk54bgYG7t7XSqySiUBTHcyACBfPdEhCGFr12Q6hFQulb6rtabLMvfel/M5C0p37wrawY0gMMtCEgIACzdIUL8AIbEQF0B0Ric0XBfkPHBlMQozUxGItHL3iK4eWdfWWgWoEEPWkr5hAiOIsrOAEYAhEJ5DnnBMt3V35yJX19e3HzzfX41A3fVk3gCUJVwX6z1MA5zAILGp4B6z6VH7g+lxOd8d718fD1MpVEdKADKAuXZtR9czwowwuJ1Mj0wVAAkDiKepPHt2uL+f7u/vz6e7u3cDoVUWRzifl7ZomQ7Xh4OME9OQXYf8Tr6deuMa+lsD7vuOP6M2I8HXcRFkEgJ2AMdUmM6pjW9vmj/E/PjsCHBnSBt4ZcGpxASEiL33+/ujPzxI18MVfhQMQSJS68BFhlKeP3/+4sWL119+eXzzFszQgxhECCAhXp6gZBZCBlREipSTdMBVA5FBCuFYs5MIiKnTJEgAQGZIxJnhZEMX0VbzpiCwba8kWKVJCRHdICgcVmQwoRDWbNF07fPSz+d5Ph9778uyJBaBAN2hqakaInKtUmodxCMBUgK8TkGR0yOGL7cTM0sC8S8C35zmSkOSO/OtfWnWNcwxQAI9q1SMjQe2agwmTSDHrOCAjuHomO4W4QjTNLz8+MXLTz7YXw9I2vwc1GTEySqSeTRAZTBY7R0ZwsB7QAtoxEakx9Pbu/txt69hBbkiRNjcdWn9SGzTVJlBdTFrRAVTRRpUGG5vDsv5ltHbfHf39hvXmZndwYGIh4ooIpkmZrjTmkFE2CqCCUGwDWjX6I/3Bqs/AREZMKQ5b2B09DCLVf/AIMlmsJHNAADAVgDtGv0RERhBAWySGClXIZYB5g76cDRkkuFwfTuOI6GMu0MpRYh3u344HKZpQoo+d3fNemA18rRuhu6+CsmA59gxwkJDlM0UEUSYa83QMQsLV1UnCmL0oJU2mVMkgcscO4fkjhFI4I4IgBSIHoECzOAeROEYlPd9mNmyLMfj8XQ6Lcti3sEjIxYAutl5WVSVmbWUQkxcAEEAzR0ZudRI+gVKAl4K81BKLVykEJF5umYjAOCq8z6Z9Txba91a78n6UyulmJAgOZFkswfI1ULNLMzXAnpt/juarUrWu6v9y08//uTTD66v9woLmRLbbl8ABQgAO4Ih29aKU4jwmBG0CNSC40RtOZ6Ob5Z21fo4SD6wuS3mSx3o6nqC7FOlbBATQoAuZlZ2w/MXzwLs3Ten+/u7ZT4jIiAd9s/2N/uplhydbqmZX5rr38GC0bcW/fd0gP9suGuIMANzgKkuamEQxJhOBgkpZQcCXFf3soLUYB0pQwY9oDGXcO0KwVRYnHjuPi+m6ogsZWJmIsmB9MUgLiKSl55CedmUVTe0VlzICRA0sgHSHcFdRci8EzgR4MbWySBWNwpkdnfXcA6XlZJBiAgGEBSO4N6xY4AjMpCD2gr0NycLpEAHTpokr0t7P8/LaV5OOTRJ6S8STh+yzOCZuU9jjYhVu9hRUESI+dGfAYiRCnJBriS1FERE9dXaF5CRgBP4KuimqnPXbqYATJAqhQSiRAUEnIgRCEzVXM00LMxXSMIqtGDdzAJjHOvti+vbF8+mq0FjQWNi3+0r8dAWYwwAJYSADpiDFoNwgGCmUmQcB4/e+mw6az8P0wBpAAeGAUOpu3HqvbsrEZiZEJlZtoP2w243HZZ9Xx6+efVqnvWMiEz1sH82jeM07YkZkMKzrY4QlsS3H4zcoEdZpZ8e7gDUzEI1MBwwdZJMYaXBpjUOpg06AIB59ufS8mcbEyMAhK76c2Cu83Ju5tPh6qCrdBtxKVICIZBVO0YMwzAMQ0TMy/Jwfui9E9HSFABKKUR0Pp/NdJxkWZbz+Xx/f6+hNzc3vXd3N+uMAVu5CeDDMAhXM1OzTGZkSwQvyhBgmp1EZs4WU0ByqCK6AhqS9z4rIgojomOb53SJOR2PD8uyCPE4jpjjTaZm2k2X3lpv5HB/rlgqVQN0QCApQGQWkBgBDQIQLrDzUQrXoRB376lotyzL+Twvy6yqSJH6rb3NqooeqnM/n0joJDIMZTdOMI4pmhQI57YAMkCYa++JgFAza33uvZehDGy7w/Tr33xWJj7N93M7T/urYZiYytaTVQwzcxFBSM8+PZ/P5/N5Nw1FXnz4wfO26P3x4Y9//AMi1FoA4OuvXpvZOI43NzfDMLx9e8dFWtNxJABmYUIBIHAI4t3VdT9f997fvn5DJNdXt9fX19M0iYibYbIWVh3VLag3yFbixhKYhJh6Ygjg6XuZiy5sv/9guGvo2tjJshRhww0TgWNcigNwBApw2PBosNFgIzHwgAiRzVqGcINSoJTd4aa1OVagEhIyEYCwdu29pxv6siy9d3VzdKLU/MdYV3RUpcj2b+9mfZ5nIEx0K27mk5dVYFtCOQLd0zEt3YdXoF9Y5FdCAUEcgBjhgBYQRLzZtCIiKbn7HDjP8+l0Op9XkRwoxZwLcoCZg3n3UPPe+hwtmAoJ5+DZQ3FTCLS2KREgCimac4C1np4c57acTqfT6XRe5taamfalBViouXUwxwDzbl2duoiYDuHq0cyH1dLIwik8ranDNi1fj3ASqlVgGIfdgETm3t209TJMux3XUgFELdbJPqHnZr7CGYlZMGA3HUQkpwr3x4eHh4d3795FxOvXr2sdh2FiLrXCOCoSCY/hDEyZJObYmpCYYL/fL8ti3RF5f3W4uroZpx2VwR0vCLDL5BsTlwCXpfUSe3/hIdkkhrxD0NEDIWuFZO6sivPrQ1YW61b8ZjKDEMCAHgQRyWVmlEIySO2u7IEeCQcFLiLEoHRq98f5fD6fz8uyaG/am6pDJGSq98UdY3MVHKSIiBD33q31RpTO9RBbv2W76XHrsfjjAWaGAGmEBIaGQQEaIMwBmD4DJJGtSfXVqtyAlmU5hp9Op+PxmDnMNgtCxEgfarMeYQCeDcmufjyfnop9l1LSTJiRSqmDlNUMxX1Z+quHuwTWp9z7aT7P89xaa/MMHuBKgDWN/lKrG8/aya27q7u62urAimxIitjV1MA83A0ARGTaDVf9ygvs91fN9N3D0ZCIxAGLjOO40w6MjskujPQDSuwRCI+1aLCXUvb7aRz7u3d37+7v7+/vM4d8eJifPRuZi0iFkFJ1E8sSCIaUKkpHJAxCHHb7Q1MzDIfD4Xo6XMkwAeCauENK+Aemfg5mjzWX4qxTOZf19Z542jRcKaw/1rAUB4P1YelpujkGg2cNsErqYWwlwY/cYQRgOb8EoFrcavR2AtMwJnAS4VIoYnG7Oz48nI5zb8jERQKhmzb1q2EAgEwBmbnWYRx26V3aWiMiSv1V3zqhcblXV7wMIgeah9OmXOXOfjEPRExlbQRI14IwB7IWXqMac/hKqVdrp9Px5DbPc29zREiqyY01oxk2hEbWIdksf/v29UVVq7tFoIhMdai11jrsp91ht08H41MZRE7OkTsbAHSz0+n07t270+k0zzOGE8bI5bCf9uO0qpNBeHhrbZU/Ny11EBFDCiBF7I7qYYnyJyyDHODQCXgarm5u3el0bADt2bN9kV0d9kxjs64dRAixYmBi7QEAkIWjlhR4C6aBat0frse7h2Vur+0NIoYPRYYiAwIjIxG7AYQ4EoEAyOq6kXMdYEIpwzTuHAyk7opUgJKIxLhco/WLdUQMXHlFiAwB39GC/EkU1cdwz6V9TYloda6LCIr3X2h95LeKB4ccvV6wBDmsASZmKVCdRg8g7EsD8KRX9mU+nU739/fn8xkI91cHJuBSLHzp7dm0X4cLQMJS61jrACiI0ftCq9KiorsBRRKtAAABAx0RttveLSwJdGbuq/E3AETkwmfZWZHAMAeihPtvmwPa5iRzr6s2ZzJI1uZ3+lUARAQzX9SrzUwtsnvTTM2s95RBREQspe6n3dXV1eFw2I/7cRxrrcRwmufWWiCow/F4fPP21cPDw+l0EsSp1MN+SrpWBXIIRIz1Q61ciClWnYQAUqAe0DOnRErnoz0XqMPu9nr37LoOO8BKPA7j9TBcFTkgcG99PlsRtwVCBKKsIRUY3plGYmAEkgEQnz374HSav/zyy/u7MxDeHHalVBIBFErTU+/dgptDMUEBEEBID25EROYyDKNBGJQygBQgRkODddS5skbWq7pJb+M6isspf8SPLeE/Gu4pULGiYNaAxsiBVrqrr8HuCIDBT26BVKTJGyD3iFx+EuqfthNFurJ7cXCjIsikqsfz6TSf1a2O4+3t7alIYelmS2+qzpzMc2Mua0cIUaQOw7RXbdZbA4eGKUUTAUBBCGusAmxMlLh4VnQlTJ4odlcwV9MwJECFhEPWFQm3Cb5109ba6Xw8tlTVk0srKf2dV2aqOyIwl3HcXV0Fc4l4A2GAPtig4edlPp+Wc1sA0M7ntw/308Pd4XC93++TzV0QTqfTaZnNwSHmeT4ej8tydnesBYtQLTQUJHIERxAiWJkbyfohESEuvmIi1IDVwwOCUTASU1kRXnzycry+jlKw1N10s989G+oN4eAdTbktoU0f7pd6GBK1CWHasbc0wxIuNROSaTzcXL+4u3uYl46A424aprHIKvHn7sfzYkER5IFIlZkgq01MITgCLMzuQEgMzkAYuM2XKR+UM+4nngVxyVLw/c4kXNqRf36ll9hqUIAsOmHFf+ZTE/WIvi7hgJeZlaNfcn54XPUJ3B2dUCAIgZOEw86OiMAR0Eyz05KtmDIMZZm76vE83z08PCtXu91IRIVKYYnA3g3J3VcVO3SNiDB4SmzJJgsF2pMvIzbDXjMjW0/SPC1QvAcQqQARMTCUwmm+5RCqZr0ty3KaZ3WstZYypMpPXlHYBLgTHwYAtVYiGsfx+rBv2lU1ZXLnttw9nB5Ox1ev32St8m4+HnsvD3dJNJmYW2sp9xVpootQd/uhylSH3TTuh1pqCcmlnYQrMLhZ70vuHr2blECmNIFIHrAGIARiDLt6OFzhWD/77Nfjze1RO3B9fvvBzbOPpvEaopp1Nw5nd2hnpQGLEBB7j968LR4QlIiEQLAgksPh6vbZB4BMRM9unh/216UUIomwbnE+z+7BUllqjm0yx8yhngVq965OQNkvAEsWJiDyxe/7Sa7o26IO21/wz05PfzDct9gFXtP91DZCQCS8IHTocc60RTutDmB5J67iUbBmNQScz6IkGgYkMy1WoF/vp9MpI97Mlq7L6Yged4f9eXw2DIW5ADCz5AKNHuabnkngVoLCVsI/nhau09AV1XiJeLIk4K23iCOQr2f6BPgOgR4OZtZayxwDeUjtVXoi37wCzrbdIyKYShmHcYi23E8+OCT2pnTT/Xk+nk5Xt7fv7u9ev317PJ6b9ln7w3J299ECCKnIOOykFiklceGFcSh1ECnp+Zasg60WT1SMmQL01hpLG3cVNnUDdzUPBEIWJinjMB6uXrz4cP/8xUPvQPX5By93u+taxuigHQBIsDi6W8IQkixHpqHuGBCBRAIkAE4RwzBdP7tJLfnco1bAxWOM0toYAEjK/2q8lIimSL6LpyZj1qirxNWq/4NPL+hmRLN59/wcHaX3w73EpgaxNSwDPf/29HEUkmmN4fau72X2gWCAgIICQaFBERXFgYEKFVBsYKq2ClrMrd0fj6eH+9TXa6dzOL5693AzvYkKHzx/VkpFcAY27725yAhmDFS5Vgz1ewYPIPIJCAnQtkh2snAXyt3QwlUNUUuClkidiBgZ0sQLMDigYCOrZdSIRZcGfrR2thZFaCxQGYSxiOfSbk6OHsrM7mgOa3+VOSKYBwZwS8pMKTLV/eG698PpdHV1td/v37179/BwfzqdzmdvTbvisBuncahTKWOddrs1gICECLp6b0BYBDG86+I4lCLAFLoomEGQN9MjYTUh9ehgwWFhEMaMMPa6p9sP9s+fXx+ePRtOvU7XXA7DcK1NPYDGqViU/eJqIVEoGAyAMDIpEynENBAO0CPAEJBBnh2e7erYtR0OzwgYoAAzWhvLcLXbu4NAVCmUNhUE6z0L4AEMzCwkI/LoUMMSsK2IyGgIS4AGNMPu2ADVgR0IQQArBqFHztoQLOVi0nAzAB0Lx4867223419wvB/xuPZGEpa08v9Xolp2AsMpUkkueu/H4/Hd3bt2ms/ns/ZGgA8PD/f399M09SurtTIxYoghFLVU4JaKiKVW7qX3JSJoxbEjpQ2lr9L6l90mf7XVD3oFfq2ojOR7po4Ks3kPx4hQtxyN1aHwyt7PYsYA0N0d3MOKbyvFuqqZu2fD2y0Lm3Qb51rrDfE4jrvd7tn1zcPDfardt9ai0zAMdap1EKlSxmFl0zpYV0vsCriaC0aRgYtwEQlQHZv2/KRri/rxw7q7J2RVhrrb7a6un+12O5mmEcuw36GMgMGCHIRcKjMRmjZmlrKOepCsVCauWYsDIVC2R5A8pVUpYAQg4lTyDCQahmG/32+iJyl4bYl1MjdElFKqBRGTjEMdiEp4mF+qru1YMc1k/hicPwIX+IkrvjyN9fiLK95tI8Ot9f2YVSc7TigiWljqEZmFenRzVYsIkRoaDqGqX371DRENQwHwWguljUlXRJQyREQ0YK6EYtFwEz72dTyPK9otR6WECA6AEZbIHg8nIvAA9EBkZsK1Wsl2r7mruWozM0AcxnHYT1meJj0f8hrYWgcDQIQBkKc0EMBUB3fwArCuOpiec8Zea53qsBvG/Tgdp4flcKWq2jGrX2ZGSdY9hEVyd1hqrUQY4C3CCQGBmQoLVrfSW++LQRSgQMh8IT9IAEBauAWVoU7TxEUALFMwjBbdVB2BBAMFplFUgQBLIWCA0AAtFQYakBnAXWdKsZQwD40IIkwc/qrDHwZM6YiGiCmZgSXn8oC22kBA2GoxxAzg4eqObsacNqsAALERBbI5HmAEAikq++2c42d1IeFb4f6XrPFPMqpvkwi35QZWiV/Hla5DJXsgq6xC+hkQanifjegBi43j3e6wF5H9YSrEqmpdRepYarhqQFNvGmYhzE0VEQSFiyAkbSMepUieHOi2XhgCgmRVr9o8AQbEiAzu3ZqFS+VSyjRNwzQlsKe35tk1QkFc4RxmlpgZFizMzIKbbCUyI7Jnj4spBMysAUYxGFwQY9xFRDeICA/1TaYibyQEgpIGwIDg4OiuFztFpjIOqKpJWMkdLWfHiAAMhEDMJFjHYdof9tdXXAsQSEGM7h5EA7FDUCq0SSFhgQAABTcIU+sRQczZMifZarvwx+uL5K6r0ZpBorXrUBBxPi+qDa1nF8vdU1CDqxQicAaQbHwQBACFGwJswrzkYTl2yOUTAD3ikmDjxWfvZyJnfszI5qcdjwVyRGytyJU4BwBGkGgcQGJmFxapJEXKACRmAZZacZhoAhhbch3c/VZvd+MQgaEe4ANIALTu86JLVzUgw4RGIhNfpmOI27wiYVk5HDegxOf7SmmO0Eh7FAqAtANIzz1mHKarbLHXoTCzdvNtOU+VfrPVRdCJABx5nRHM85wFV6GCwoippAfLsnhXm1s0lUDhGuQAAFJXCFc8hruqEREBq+o8nyxCCHPWZhEaIEhUpAyT2IoCc/cgJqI0v3WIZO5xqSmOrLowRng0795JZE5IVNjMwG5pgxhYBBE9rPcUN5ZcIsxyh4yVBgl59uBpsApg4RjrcBRRkNx1iUBmJqqQTfRw0Bk8tWsUoCOUAIY06WMkyXZl5MgEPYTQgcKdwM09+5R/8fG4uv8SZBEA2JAFFyh2zobBiCi4sHutdb/fP3/+/Jub6+P9u6aGTKXWpZRl6V9983D3cLw/Hh/Op48fTldXV4UFgPb7fTKc392dHh5mtSCqFhipy73OMTL3M2Y218yoASPAI1Z6f2CiXQFySATkGMDoGERgEN07cxmnWochtQAgMOXyIq+Yw2VbzY0bMdKGKRAT9AYA7s6GIIyIFDDWoRKPUmAb6llX1X6/zFDEwyBV0hEj0MzDkZnNjALmPhNHhBmYd0NQopZ7jge6OxCisBCZAaYBRChi5UKq+vDw8ObNq6XPXAuSOIQDRUCikQGIgcLRurfWFFOBzDx1hzBW6EwQIhOxcCWS7NuYeYtWSoGNPaMBRFRKgUAL9xSaLUPek8w8DGcIioBwRizCA1PJW4gZ058zyNybeQ83SBQPSsRKQ96YON8Teu+7G3zneFzdLyXXX3G8pzm/deRDIYhIzDQiSOr+6vrFhx99endvXb/54vPTu/tFraeqkIEeQ/2tRZzndrU/DMPIzHXFxPrxeG+uh8N4db2HJMxsiCKAtC9DYox1mdlwt+HugYjmkBeSAUspkc1fQk9eumsgIAOufmMCgb333lPchxDZU2PJwtzYjNe1s81zQ4yxrufZWwJmBmY2c1UlosIy1qHWih6zRUCu4pDTX3MFgHAEh9Yt63IRKVAs3zAQAdWNzYGywMMy1DIOpdYgZDVT1bAA4ELjOA5DCev3D2/m5aEMlUQsHBFVfcMqokgpVHqzeZ5bdNWWPQAAN+sp1QaOwrXWqcgEwareFu+9Gy25I4Wjhvu2nAGuwCBmDuJEAZZSpmFBRAgBoCLjOBxqHYk4H5n2PEQA7HmnAee8FgAwSQiZ3vxAYP/ZMdPPjvI/Ux9sbYqtyCa8FMDuoRZENAzDJ598guFFKNTOD8d5WeYeYcAM3UBn8Lfv5t5eD+9qGStXd8iGfV/mUvGzzz4ddhMzF4bI+e7GbyRGEo6wxLYh5qp54dqG57KTzKLUE6UAzi0CuQqxBAUKylDP97osfVkWSPW2IDPP2uPSAoLE6FtT1Uo4DAMAtEUBYBgmkZLThqHU3W6XPFb0SNDveT5jRO+tzUvrM9jaZxKpAQsiBoKGqndE4DKEz8ic+EIkklpqrburnYg4I/mqLwyEtdZhN+x3I5JrW7SdW2cRMTPkNCZC7Q6AU91Dnay7ns8Py92ynD1UhAmjJfwYcbc7DHViUNAWnc7nfj7NvduD3uWOdEHkjbup3dzUWte6BcDMjsfjor2UMtWOiESVkMe6t/1J646ZI5DSJFqABUWoFGYhrxMTIXsa98aqdv0XHk8akT8j7r8n4iPiu8+OCDMnSl8Q3BhrpU4jY4rI++n+4e7du/l0NrO29Kv9pKoJ7b8/nU/nheik3VvTvoAqEMNuB8+e3z4cl2e314AMYB6gG5E8l3lmjsjYYVljHS8YAQCIsGVxRJymadP8gIQGBHhmKafTwzJTax2AejOjOB5PiX3PcM9reXV1Nc+Jij/vd1VE0kCLSA6Hw3xeENHdp2EQkWkYh1Kzf386nU6hiQZT1fl0dvfCYuZ12Gesl3EgAger0yBCE0mtXMqQyn9lLCJCLDLU1s0RksJU6zgd9h+9fHl1e11rbX02M7Qw6yzo3U0VgihQpI4FDyN75UFcPfppgVAmZqYgMz+L1Mp6c6hX+304tQUo3BY8P5zBZo/QeBQ9JaOCNgowkyP0rmddrB/7+WxEUTsRE0qt40CEVihIvERE66qqRFDH4kWi8jQNwIWoEKCBudMqEbDCcr/dYn9PTOyHwn198NZJ/Gk3z3eb7qneuTrExIprw0xzL4VjKYVwV6u08mC9P3v27Ff/4TcQsR+Hr7/86u7uLhYTrllrtqbqHuZdVTt0Aw+QAA9oHovZ0o0mDCOD0HDytHHK+nRNY4TStxXdHZETFptIie2jIDIhEwBwoTLUfHAiw+YzZA/+dDodj6c//elP9/fHlMtqrWWee31zyBvGzI6nd7wqQSMCt959M35qaUVGJAQRUVjcffYMdwjw88PR3UupCPzm7tianua5DlIGoUI3N9f7/T52E1ceER1Bw8NDKpZxACSLrm7dwiNQuA7Dbrd7dnMlIuczdE3OlxJBbGA4IpmG4eYwTdNkFgL+ToDQwBTNI8LbHH0BCIFpKny9HwnKmRW6nVAZWugZAHgVooaIGNjHgle7yswW0ShscfIW/WwAi7dEiAg6aKUYGQoFuAdp0/kcYGFDDEJRoRCULCQ0hYAcFIEj4lt5M8BPhBW835n5OTvF92c1saIaHimtmNyTZDaI1MIR9c1yRObD4fDpp58KoC7z8f7h7u6uhzNzHQoAOLEnRzyJw2Fg4AQW0NW7uUZ4FjA5YQFf+Y1r633bT2iVLnEHSV53bPiC1aNhbXiXUnL6rW7QAQBKGbJnejqdvvzyy3/6p396e+cAUCuYwTDANE2Est/vDocDAHgshEJEtVYLAID5vJRpvLp9rqp3b98ty3JeVISoFq5VVKBpoIuUHZG7ixQi6W/v79/dffnliQjKCNMOIhwRxyrqlvf1JhQB+cWCkpl1UzNDolIGrsM4jiLkrkgAlp3LcEDBAgADl/04Xe33ZdxH72C+q/VcSgujdRkNyoqy1Gms1/s9UGGY23keCg6FTouvAsi0CjpMY92P5eowikiEzzOYysM9zGzuru2MSCBepRB6EdhVFpbeexhwaDN1CqMKAyM4gYMHYmQGarH2VIgRYJMQ+8nJ+GMyExvsHf6SsnXLqL5zt6x1ZGyIS0x0MVxdXRVh3e+PD7vldN7v92WozOwwr3YDREgCQOHQRA3E4LwsagbnDqelnZflkM6AEO7BjpSogAvyJ0c1266VH46Zi3t3MGvJkFrV9REBIAeIqproGiJCiq7L+bw8PDy8evv6mzfeO+z3cDiMAHB7e/vxJx999NFHn3322ccff1xqPc937sBFdrvdMvf70+n+/v7q6mocdqr6xRdfvH37ts3z9fXh6uoqUYSvXr1y191ul7sKEUXgv/zzb+9O51lPZrADIIYUJ6tVLsJDyTenIjm7AABNpCQirbL70E0DycIxdR0SYojMFERp/lEJBRA3AzahHEHkJu2EQAWFgkKjLQuiLcu562LWIzpE3noU4SkVwJC1vPoqUmTgFqau3d3VNfvEwtz6bK3p0AjQrUd2Y0wzZe1deu8yBIaBRy5osUK04LutxJ8yWJUt61jXiUduyE+L8vc2kUudCpd5MF04yYiIHm6mYQsBVJYWx9evX//rH373r3/64+vXr4/HIyIm4YOZ0+eyN+3qDpEC9A6gHU7n89x6NzWnCCQADefs+0O4rxCgVVmZ8u6lbeFHBtSsL7P87T2J1cyl1krIZoaR2z2MY2Xmuc+Hw+7FC9rv959++ulnn/1qnudpmm5ub8Zx/PDlh5/+6tNxHN/evTGIaZquDjcPp+P+7v5Ze/HJJ5/d3Nw4xO9+97tvvvp6WZZPP/305ubK3duxv3792sF2+xEAuhmRUFDd7ZvH2+O9tX7YT/tdffnyoxcvXuyvd+M0lbEAQPRs7Q37/f40n7upqnsEi1CpAKAWx9NpGAazQGLBEiEAEAZbplcg5Lxo8SUiLICpFBki2YJuwohQSIbAMjd9eDgC0HxurS1qLYFDzPyYGOamALa0sxoHQGstgYBro6aWjDV37X05t6XMsxUDx9yXulkiP91WIiJ7BBpgIcA0lcFUwQrcvAi2pP3Phfxfg5m5RPzj54SNHfL4zwHoAZeGIGBiS2oty/n05s2b3/72t//8z//8+eefp+imgRaUSLFdMOvRTM9tUfVAkCrglnIJmmP/WHVVUosmsYIRYap5WgCAsNo2IaLr6vLOwC3WBb61RsLDMJQyEBGT5Cg3ApflzIzjOGlcH0/Peu8vX77827/9208++eTu4X4cx+vr69baRx998OGHt7XW++U4iNze3l4/f1HevVOA6vbBy4/GF88B8aV2GYdlWX7zN3+T4f76i9fDYceM427q1nrvwlWkvjuePvj6m0+++VrbctiNYy23t7c3V/tpNw3DIMK52ANAqXXa7+7ORzNTtwhgLiISQK2101IcCQDGMogUR4NE2sLq9NmN9Nxx1rXFFMwySrCHghkLBihgNYVl1ruYI6J3m3vrZupOLEi0kkEQHaG7tUUJO1Bz9/x6HQJS1TRpsIGAnHIji3YAUtW26HnpZuaA2E3dPG1v0ISCEYERkAOZEdO88eceApeN/oJSgO+3+/gpR8SlTl3jPzfoBG8FBiIKkhKdz+cvvvjiH//xHzPW3717tyyLuyu6rWMa7WbmYavkogdhIQFgnxc17713N4gaoe6Q/gpMuAnJYW5/ZraJNa4nyUiOsdIRdA13qaWWMT94NsgxSFV3+ykT8SCMsKurq48//vhXv/rVp59++nA87vf7m5ubN2/e3NzcTPsRAGqtKCxDhd3u4H6c5+P57IxACMx1N135szLPdTdRHQj9+uZWSkEmGYRbI+2ICEF1N92+eP7ys0/RdD/UwvT8+vpwtYPVrWnt50plIsp8TLvnPSAiwzAkrqu5FQdmRhYpY5CniTanpG1ExLpwABoAqCNyFRS1FmiFClAjZDVcmltuAuZqTsJ1HNiEiC40gwyApj0WiAj1xORrfoeI2FmTYSDEQNi00zJr994tt1mHwGAL7xZNXTaK+AqnQPxxNuqfCfdLjn4J9+Sa/SWx7tnpW3PlDRSuAeY9lbqCOICIgd++vv/8889///vff/XVV9nXS4Yyj6touoVnPGf8WTg4GhGYLUv2ScbT6eQ3dR05p13teuLr6AM2yDts4b62vREyX3e3zGe2z57OQZjKHBk6ZtZU3W2aRhE5HHZE9HA8nk6nWmuABSRTlCCCirTW7u/vd/srh5BaqTd3h9ZABAin/c7CLfy8zDmAdMA+z6jYTc/L0lo7n5f740M3q7UWrPtxKEy73W632zmFWzezUiTDHRHTkfw4n5dl0XARGcd8+KFhABMRi1SpIxgwETrhJtnl7uSubtmzmvaHMowYoKq5guaXY95X0L+tshj7/d7Muq3S0onr6qa4jpbdIUiDaBCpzDzsJiKKkg4YhOmczQVgvRallBRaK7XKUMdxquNEtKoj+0ZX8NUe5y8Kd3qiFh0pAIk/BqT5MTRxqmyvM07DFexj3RbtyyCi1sG8Fvrm1eu7r77+5k9/un/16nT3zpZZ28wERlCYSykWcJq7GkitzuBmy2xDHRRC1aLAcYGlS9cRmotIQOisUEiIoUdEJyYmyUXBHdSDyIkoECgBZMRMYsbWUAmiERTGUvLirfIGyIA6jOIGVtAcSx0C4+F0t+ii6rP1h9YeHh7ePCxfvjvu9/vfffXK+jLW4e5hcetfffFlX+bXf/jTs2fPhmFAlqW3HvDVvJAIEHfQV1+9+vqrV23urt5na/MSzU/H++htD4Nrg6a76/1URCCQ3AKcqJRSpspF5t4e5n4/txYIso/oWA8s14ebj0u9YZoYpdSB6wQyYklIABGzu+P6n8q2n1t4CvfwprhWnvSRL4tC/pNEpNKNP5GGWV/HDADq9txpS3Ets+3vRGv+zttCWWrlYVAppeyVOAAJVFAjFkcCXP1lIlYTnIs8TPwISviXgIhtp/tt9fhYeZyYoukXByLwOJ/Pb9++/cMf/vDFF1+8fv36dDplOwIDSvmWJFisymmQkGsmxoBgNlQzSB2ihMGDr1+6Wfo8Ajqm2felMfrdIzb23QrP1OY+0OrF97hHMTMhllKKm3uqJPjbd3e9p8bUH9++fTuMu/1+X2v98v5eWx+G4WZ/mE/Hb776qs3zOI4ffvjhMI2lVIUAZBkqF7GIu9PD62/efPXVN3dv7ufjuS8qKGOpUx3GoeyqDPURo385JSJEWUdjmbBthjAiCCI1hSbHceThOveQWmuapOZAgJkzVC5iXTmVA+R4clzi+AKsf/rtXfZPeFKw4TZm/t5/tW83x9+L+6efMZkSABCeEtWJTkt+Uzoq/+zjFwv3PLbOzPoFAUC4rV3tjXJxf3//xRdf/Pa3v81wP5/PqwELoIg4hJmBBbgGYIQTEjOP40gBYeDMiNoVlmVZlqU1pjSmgYxdByLip/rIT4D4Ty5SHllLZT6wqeyOl4dFup4icqExRkdQdVVdFn14OB5P85s3b169evPHLz4nlHTNvm9dVQ/7/X4az8fj3dt3YCbM4zQxsyNaOAhPu0OdRkQMpru7u7ev3r55dby7g1C42cPt9dVnn34sN9d1d7sbSi3IgB4aJlBwRVInrNw9b/vj+QQkLGOhki3wbNoM+z2sg4UCsCKkk/mxfTucpWa6CRA/Kh4/Deh40pt+L+jhSZi+FwNPH5OH/WgS8vR1nr7ypvW54jGzwvpO8P2cqepfeTy9uZ/ud3RBApvl/1+/fv3HP/7xyy+/fHh4WEurIswMHrXW8zIn6cM9ACjJXoWYx0HVNXpm3hGQsozzwiICQoikodAhxCsxIMa6wGdD6PFKfPu0TdUj4nw+11qnaRLR7Hz7upunnDTJwDum9OeIuYtIERpKHYpcT3t3ZxYAGAsil2eH68N+amV4vr8eagGAeZ5776fz3JYWQl5GHkGYiRiGCQ5GCiOdAPDZ4dkHz25fXD+7PuwPu3EcCnOIEK2JYtrNUwLRlraczksSf7lMVSIc85tR1YDNqjeNMRwjPDHJiYTJgzYEFoCb23evaS64l18jni4fWRc9xYHD07+8v37/cKcwd/L8aLAlCJdlJ+mzmMYrq8nGdwZMf04e9Zdf3S+35prMxDoQ8d7d43w+f/XVV59//vmbN28SPRcR01Baa21eLsVT9sxxHbsgiwhUAO1LM+85at2aXEVHK4WRKIzdeyIr1qUhlUY5mdKrSsllX86esepjatR7z0U6zUvcTYM4giKIsNbKbJkMqGoMI9/KOAzXh5vj8ZjtkRfDnpGePXt22E+hVqXs9lPuHr3387zMvSHRuNuXfCOE0+l0f398uD2ejjM6TOO4G6fnz58XJgIEUxapazaSvBTEdAhzPy3z+Xw+nWezCDY2V4u26Dy3NIFJ02TmFXmfo+5wvIQlJLNrJURT+NOIwW/9/GRjjA2SF8jbr/h0PaZLuMNjCoSI4D9S/cXlNLY1arUaj7xN4qIOc8GZ/7zjFw73PN67oTMVi4h5nt++ffv111/f3d1FxH6/r4VPp9M0lPP5vJzTs84iVomJ1AvC4BVN7n7G1FcBRNCwZTnPM03TMA4Dozh6CvxGhEZwYIQRERI/IX49btDMLCJb7ru0NueieCnf17I1zJ0B0qqMBwEoDrtd5WKjXe32n3zw0bLktoPmTARX+8N+mhBxN06Hw56I8iOQCDKTcBCqaut2Oj08PJzevbs/Ho99UdMQIkaa5zmsm3X3oNUWSohScgW6m5otPYm+52VZmBmAVXXR4N7a0u1bet8VESMwaQFBsGE5n67BK57ihy7l05x++/uj2+blMbkk5+p+SW8uj6HvMPAev+ptyOkWF+ZqmoE+2VhiFYF5PH5G3P/C4R7fRh/EZoDm7vM8v3v37tWrVw8PDyLyySefjGN9uH/36tWroXCCZlOzJdLIHQKRLIIYqkitA3gUFkg1HAYAaK0dzzjupnFUkJTvQTRTJw50NEFyBPYL3wwRY6NpY1bAtilWL8tyOj2Uwkn/29IxNDPETp5Fwgq0rFJcrbd2urtjLu4uXAHAtQPRWe/78TxIsWGxudWhjONYy1AnKlIIydSWuemyeOugJu4jSakYFO4O7pXQgRiZBdd1fa3gQ1eLg3Ze5uO8nNvSe5c6qkVX711VPe+KwAQdZczxNobEpFRuDPq8+QFRAMC/nfXF00waIfWaVicBxACg9OS9PN591cdzenx6ApjwCZLqeyLnMWYuNcN2z6wGLGt6GZfb8mcv8L9kuEcEwuOOti4DtCbB5/P57u7u7u5OVff7/ScvPyqFv/yCHx4ehCB7uqqa3EPavs0IyxJ2GKq7l8LMZOQkAADNdJ4jkxBCwXAzAwzR3GNBCQg90ZpE6AFM6/KT73jJFNdKYJ7HcZTCBUquNxaRHksETs6rqlKYqgpSZWGksQ4YkHnRUKbMwVZl4q79PHPA2aJx4/N5RdhHtE2Oz1pDdYkgRwtPUXZtjRhSZnBYcTLu7t09IrrqPM/zMs9L6127+VC5uamq9jR0p0AmEgt0IAeKxxYdxcoMyH7541qbGQQ8Cb6tLoStxfzUTSA7MLBlIBkDGAG+ZUS4jnGevs5jl+n94MlNIGL9DwBWgvG2OSQ+BB5f5+cev2QjkojCPFfoS7WROKN5nlX17u7uiy++AICPP/74P/zm16VwW85///d//8nLD1+9epVJRSkiIvfHc0Ucx9GbI8ZQZRwKIb6KqEJRHALcYJ7nhxPvz+d5vx+GoS8tvynjgAiiTP5oxSoBIKLqKsKx0We2qZbZ6XwsVfa6U62XgjuxUiJeZcifkwxVRSxUmG6urgFAUCKCAYds5YhkxZHEtuU8xwyIaCksZRaQ7oXkFpTq/0tfliUxDpluCFIVLoMw5/zOI+HsZktrc1tOS1uWRc2YOQfPc+sPpzbsO0ktZQgAVR3HXQTmdUFgREjXXyKCWCdr8ZjJrxf0vdzvcpUvna6tzw2JUro8JgIA6eK3vv3pz4IO8YIbhyfpPqxy74+v/8Ov86gS8EPHL9mZyc0/J2SXwsU3wZNlWR4eHpZlqbU+e/bsV7/61en0kJfczLIJmH4v7i6CVTKdsMIsQrXWCDzsJlft7QgRptmfsW6rRKgGUKQOf0SkLlqmMRwphLJ+U5si4GXfxAjw5OnN81wKE0EpJcLVjUMQ0Vg5Lh6IkH1T8M2OtrdlWZal03iTjVepXISHWpEo72SgzOusM10Sqt1+zJut4CwQnXpuPosahKu2aAY0MDoQJrwuu+zZh120ByAxm8bpvJzOsyoQCXNBYkSyAHUDo1yGEZMTF7S5C7r7JZ/Obg+sqcsl8J9c5u8kOZSLwuXv38HSPv31aRL/E4/LF7W9/nfPKY+f1Ib/Vrh/bw3xE4/8nE+na/nZVLXU1RB9mqb9fk8Mh8MhF9ebm5uXL19aX4hoHEciMlMzE0q2hLoagBfmsQqYHw6H1vrDw0MYmEMENIXee1PPZdvdwhUgilAQxGptDxHZi3NcpVu/NQu8FNO9L6fTQ95dIuKuQeBoEcm8VEySH7g7IFApLEjG1gFba+g2H0851gGAZE8nOmNVYQcwQ9DHks5az3DvvfW+ggdzV9kuCAN4IKtrMpXy/1mtRgQSIRdtej6fT8eF6ljH3bTqhaBwSRvhtWkNiU3nLefErce3yk1/NxwvK9cPxfGPR/B7//rXxBhsa81ffHyLmv3XnxBuUJlLSZ4nSES73e758+dtPrc+E9Hbt29L4URcffGnPzDzNE211uPDu65eB0mdCWIswiVr2aD9fjoej0TkHpDQFkh1ALdwc+BANzB0BPB1W/MIJgk2iCCmyz6UyPIgXjuS7uruy7Isy9lsFyFmhquBqcejjtKqME3gK6ADkAZEj0K8vJu74QXv2nXNNDJlCsIUac2s3V2PfWUA9t7bsqg2AADCYTfkFiFjKUM18OhJHl8j/rGiQ0KAZrYsfVG73g9XV1eHq+taR0AehqmUIV2zaYWH5F2X3Y/tE4E/7aZfQvxyWb97oX9itLz3gJ8bXd/31j84Jv+zh7x3En9xrF8WANw4qfkXEUFcJ6y5wMPmypvT+Izy3W7X5uV4PNZa3V1qKaUAeIL7cprDzPM8p/pLDxVRZiACTGuhtI+mVb8p3APRV3czi62xBbH23TeEAq44LVfVHIet4OwV+wUIQGkHGEEBFoEQQATgkK5JKedZqiAiNWzae7PTMi/aj6dzykhRkW0huDiLqLuDrSu9qpq2iOBCwoKIXKgMQ6kVUiEMAYjMVnR+a6qqBoBmDrosy9IbAI7jeDhcHw6HYdzVWpFL6rTE6kiBEY4egPTYLcHNIwA3w7mfdrlhU/f/8eB5GrI/g3r0nff80X/9SYpi74vm/aWn8q2k7bJ8uruFpYjFxQug9XlrdTfEvDyH1tp8Op9Op3wYCUdELQUqFuIcWUzDmPn3UKr1jHU0iGSspYc1I6GFp9wpogIIYiCwbeflay64Lu20qvuapbKAQt48oXlXrKkFouNmA4qElELEEWDhgAQIQiKVCCeMGRLO0E3VzulrwFsjCGmdtmyLM0UEeuQ7EgFFQQwREhEWcnA1VzeLSD02d1+09959I+Z64Ol0iohxnA6Hw+HqKiXkp2kPa/8OI3yz2n6c0UQErL6iv8DxS73Ot4+fHpM/gav6V+ZSl+O93e0y/nX3RMQMw3B1dbWcT2otDTwiTEQyob+/v08p0HBiZjdv2ksppRSztWG331fVBmHDUE+nUzp5IIIjuEUzDXULDethxIzsadSKZOTiEUxETBd1dswfkB4X9TS79NAEJMNm0+CujuSgiAVWlNKWuTESEW/IqrUcZBYgDDfv7t5VAyDhKrx25SwiLX8zbXBey/sEDyU+CgMh3NW0h8Nq47auJsRcSQBJPbrasiyllGfPnr/48OUHH3x4fXOz2+1qHSzhA49Kd9naW0vSp5csH8Z/UYPvpx8/P96+p2z4i49frDOzotttq+svb5BiV1syczgclnaeEbQtvauHu3uODC8UzGzA994TR+mbf3QpnOFQa2Xm9BgTwTU0kgDubqqUsFZaw52ZAzAimFda5tPQzBSjlNJ7N1vRfBnuW7Z9QW7kgmwBjDlQvAzJY82/k4ouIlI5ALD0IMREba9PXyV48mVpM+gW5tQKrbXUYQgExzX0Uu40Yf3ZiMwvlop4gC4t5Tan3Xh7e/vhhx/e3t4eDodhmIgo6eGZ42/l6WWk+h4kyxG/R3Dxaah9N1ifdiZ+JDwuD6OfGbjbOf8yQf8LNyIBISV70lsLmdwXBmKmACzAV9f78PZAcD5FZVvO58Mk/cSVg2FhWJqf1DoSjJWrFEZxD1JBL6f7VnAMPyKSqi6LHQ4Dc0UaedhhKbWI9UaCqJo6tel6qdRNogwFkcEECREQDEIjyIiECRSjCoCDWWcUjLac78ZxDKgBAOaBGkjoERQejkCATswoCI5mZgQhhEWJEJ0DKBhxIByIe/VACMMIcgfzcJVwCsBuRASFgQKEo7INshQYJnGIFkvuYFUwwsO0e+/emTE8SuHTuam7qk7T9PLly08++eQ3v/nNixcvDrsrEUnVNjNj4Vx3IoIY3FNzyjOpcYSNRh3842aOPxxvP3HR9p/UMHw8crf53hd/Op+9/PzjILF/D8wMbJm9iBCOcXVVmESot8rMfVnOu/M0TWWYkAsiIRKmSq8k2tNbm1Xb6RTzcm5t6T39SsHCL6hoAGBGQnYgcApLEmB6jASYQwfEEOA1Y3EwM/a0g1wr7ETJAoCqR/RaK9DmL5HVCCq4MFLQBjjNFjWtmwwoJJKzB5jnWbEHUkQEQxiYEdKlqzQMFBGO6crIPBapTEVEOGvc3DAhICfGuBoHg7qjeRYtEfH8+fOXL19+8tmvPvzw5eFwLbUgcER3d0AnKjnf+KFcIr1YcBse/f/r8ReI5v2Z4/1XQ/TI1gJKepIyD8MgIstyLqVomy38+HC+ezhOb9/dPbwD5FJLBJr1ZVkIBSnO870btDZ76LLMDs6FIoI3QghAEDGjGJuxpnkTxNpBjLSmA8A03IMIKuAGCr4uIRTIlHq0SM2UgobI9cCz14ngilgoPMGyCBGrExsgkDAAkKET80q+j7Tg4rKurGEARBwhWAiRAAuhu2s4UHARHosMksV9ZM18oThYmPfeTTc7QVMHoDrsqcZHLz/7D//xP/3N3/zHjz58OY175gJMYWT2CPR9r734eIkCYvPn+nMQ2n/v45c9nUclgn+joM8GiHlAuAJVYWKoI5oZ18JcVBtJbRrHZXl7f2ptvru7W5ZeV23RFhhLO8Ux3J3Ya5V5ht1uV0pBpLS6SKsSQsL0zSKiUsIdzCLCAT0wE5IEtwAURN3azClbC6m9FcwAYKrA+GS/9EB2NAoyCEC3QAAMzx4eAkBQjpNqITNmaW110QCktYsZgQXDBUCYCyEiCmPy5RydmaUKCSERMnmyeCAiwsE7+AJmDgjsAAGuHmWYrndXdXf12a/+5je/+dsPP/5k2h8CSR0YULhC14gwXyl571+mjRGBQfFzhNL/Vx3voyF/5vHLKgC/fyAiPNpQAQT01HIPpDJWFkAaY1/GSYHPXe/PzXprPbq+QxLz3to8DIMI1IHa4sNuxJzaUOE6aLedAAvWUgZhZiQHIiylBLurGUK4ozuk556CSsqaGSgG9MhCEIGRgBBZEMhD3TfH+8f1xbMBn/l7D8umTIK+IW28EUIIGasLloqmrNY8QY4GHu7OSIwkRDmQA4my9uMDACIl/ggSd57js4joZovprOaIVApGShrzfnf1wUef3r744OPPfvPy408Ph2uk2hUcPICQCfN7MOuIuIHUL6UqbMv5Ksf1/3ur+088fgKTCeDSiLzU6X824n9iI+nygok/DWJKw+oAwExUA0kqMhFxHW6Dlu7nxW2Z74/zu/uHvCTDNB720zAWs6X1RXCs4/DR/nD74sNx3C2to85tPpkuA3Pl8B4QREzaOniOujyQMC20YE3BzRxAIzgikEpS1JGSAwHhDOFu0JuRACNgCmlHBJo7ATkiA2GqnYUjAPmqiMnAKEyMLObdtOiaYftmfy5IjLTCGdhRpIikJndqgod5QBowhpmpQ1Oduy6t9cWYiwcCkHC5ffHys1//5qOXnz57/tHVzfNSdx6soMn9UffEIK3JGCJfEAEeAAgXc8VHmOO/Re/8lzn8+2rTn3U8TlV/4tL+s/umQYlxDnJYlXgNAQCFhYwYEEXKAcuHwU1hV3he+qs3r93aNA3Pnl3XgdPYo7Vep3Gc6s3tB/+3v/3fXjz/kFm+/NPvvv7yi/u3rwRMIHJGKcQOqwlzIPFqBu6XUmzFq5hFrNIDkojywBwrZXnau1HPPj0TkYUHQCp8MBEhIBMSIdGjEgQxEwERsjAAmoB2UEbliKAAyuoh6xl3h45MJEjEZE4QqrpKVyJiYDiaaet97n1uTRcfBtEApDKMhw8/+OTjT371wUefDuO+lMkBHTENTS3QHVB4hfsz5faSc6ktXDb5LXx0VPx5l/dnxsPPVcz4udnLD51Phvf3SKL+IinN47tutT4i54w6wh0AiQI5EAEDkWWUPdCzpVP0//R//38086+++P3du9fLsuwPNyJ0fX0wi8P1LWAZp2mapsP19X53ZXo+Hx9O929RbZWHNA9ApEBHIKQghxDCpGVEBCB6eOSGTkrOaKEWQmThq9UbcoSrBasTMXOCyVaga4QBCaXR2Uoy2/r4wAlkwBT5QCA3Il+HBsktIkYE9HD3ns4zTEyExAYR5hYGif1CJMQISEMEVXUUIMZAQinjtL+6OuyfjdOBZPTA3h2IkDnw0eoCmAQJCTyydl6/JwDIdup63be4+Ouv/r/18b1L+5qV/egTv4WZ2Uq3H3iPv3D++jhYiHBAAOBk4HoErPJtTIil0osPPxoJEJiE/04IEV6/+vLh/ni42k/T+OLFhyRDHfZUduYAJFyHaX8gKR44n+ZDFUHicZznOWKVe/dHxDal9Xb+DGDuborKCdBf3MsT8HIk9AFR3V27hysREAUyMhdOMaAU5sFcJhgRkYBZVr+AQEQQ4YvjMSPmHHbdUjwKs3dFcEYiyFktVimJh0k932VZtJlwFXZDXnoDIBnrbn99fXNbxx1TAWAPIuFASlVkNUdENcX0OrIVmwlb/wCyjZ7Q5+34uRzQ74bLj8fJBc/+s97l8el/7nl0meZ93/Fv0nd/eny7+ZUWZRtYEiIvAgISEkkpsXv+wctxdxh30/H4cHq4e/vm1fF4bq0N9ZNAevHBR/ur24CCVABgae14Wo7nPp+7NYtSCIXQGNZdg2iFgq27lqM/CkMRgGVKg4iqDNDdmSX1wwCAIlC7h68QLSJlLggGkB4egGCInB7dtElEAyWiHCggHNyD0ZEeZ8ZMG83HwTaW5naN1rsNESlW0VZrZmaph5wAGCBiqeM4TtN+GHZUqjnlCScKK57EIf0ALHF7RPqrrAYwv8ja/iM5wpY8/RJv88PHd1uu+eu/ebi/997r4omr6lNsYMl18WO2hvvDFdFnf3v3VvsihHdvXx1P91999c3cHHG3NAKuUqd3D3P3uH/75ouvXr27O4n2m2HgwoLYM9ZxayVnKHn2ArfaLPvgZk9+FmYVk1rXLV5VVy8cjJWB5shE6GBmbgChmcNkrDNjas0jIgMYAmHkf3lLIDKumslOEQnmtIhIbBqgR3hA/qeRAsXWWlN1qcSAJ9dw5IQhjbth2ksp4egWQMnEi3iihIsXGtx29b/XrysgOzN/bRheLvQPr/H/tpH+Q+/77xfuT89g/TnWX2C7GS5h50CllGk6fPrZfxhr+eSjl7/9l3/8w+9/9/bt2/v78x//+KdvXt9Ph+tnL14e5/769evP//TF3etvqM0HBt0BMLIIc3FrGEQUGczgsbHDth4UrEgYiwhH8AhzI4jiBEhEgd5drbgIQeqcY8qoI2Scg1pErs/AzBm8ZL5OTAEsMILCBdfPHN4BUnviQtn0RMJwRFKjHMEgDCIR/Kra1LspWUn1G9OU+E6cEpmFhQJKeAQBoDtuuqG4bRkJ9v2BCHyKH/8r+5Dx1+Fq/+2Of6dwf6/RCRsd6/J3Jo4NLRwRXCoCIcntsxc3V4dfffrps5ubm8PN73//+7f3d4Dl4Th3k6B3X379+re//90f/vglm93uhnE3qJoqDSxERMarz+e6t0SS450owCDiAjSHDchxIXxcElkzAzURydQFABFlFQAFzcXeqTNSmBMgAQpx+lFePmPWm/lr3mH5WfP7cUILhwhzJyJP4z0EYPJ0pQWKCDdQX0khZoG8+qGYWWvNwVkGQA4KQAQmWDWoN/GhTJDek1bLC/RvHQH/i47vHSH/e4T740QDH9GFaxt4VfzBBPq5p58YqoPUOmKphysCfHb17NNPf3Oa52725u709uH47u74zes3n3/+5R8//+pQhx3zUqS38AoRiL6WB5QjIA/AgFVcJWATeo4naLvEk5it88cMdxFBAVVf5Ss86fsAzJBCtqhB5FsyExHEAOiAgo9UCcK1hAIEULVwiySjIKwsPUqzYw+IDm7gSKgW6t7C1ELdovXWWrd+qSZ9s2NwCA8C9CDHdaqcEe/r/Cszevz+TObf4qL/8D/+TETkk4f/3BHYJeIv1/rfI5l57wwuC2dEXhbkLN4CHBBFkCBMKdCsOeA0Xn30Ib94/hEwLU1f393/3T/98+//9H98+eWX37x6s7SQaOe5zSK9W/ha4SEyoie1HgkjHBAzS/H3UXkRARc1pdxnUlPc3dEI0XQxXcxGD8cYUQRSRZizv5TyLBHh+faBm/QKBWRBTCIJvQXLtT3rQrQ0rAeMiO6mpqqqZhHYez/Oy7wsS2+9dyJblqWDC9eEoyVQufceiB4d0IGDeJ2mbX2YgC3Wv3u8Fz/+190P/9ZpzE+BPf5IlQz/Pp0Z+PYXkVG1Ln7+2DPKgq+Hk4I7VGE3YirDMEx1ICKu5XieqU7THz+/u3t4/ert8dgQyR2Wpc8yq+rWUVlx6Gu4Z5s/nrDrv3OGmWLBo3TtatmeqJuOeHGWBIBa6zgMAFvf/emrzYbhqTe2tn6ebCMrdj8N1wlxFbZFAFhpWSnv6GYWrbWUbJ97M3WiWHo3ApGndvKaVkaRIY0EmBynSMEwIsrGT7Z61pP8vivl339H/LzjR5qA/6uOp+cjeaPgpXf1w2j9/DYUnzby3nvhbz1ly1y/FfGZwCRRFRiB0MLDFACScdzDx1qlFnXbHa4QnBgJghjU/fXD3f/83e9//8cv/+f//MOXX71To1qjkrTezwsfG7gcGrKRBbSIDhGClqygnDP2AAwQYiAH1YhIXbGCkN1Ai+jqiMiFlkWrDCtu1mEBw+iMJkQqICJIlDaIERbIYcq8V4XeAxGAyCOz7XVWG4EOboirEldEcQpCAHLT1vA0+9w8grq11mxZ+vF4tL5guLqBNseJpikiFKBhnLxXCqphMRMKRhOQitUV0XgYBlqr5JW9t16Lp5c1ctYXFIiAht/Cuz/eIRkP32GyfldPPSP+L+isv9e+y798dyHP++mHXv/y96fn8P3JzHuP+P6Xo8uY5jvnAbExMB+rveQoxaaeB9vymdIU8CS9yQcXJgIIdPAU1A8EIooiJXR59+7dv/z2d//1v/7Xr755pQ7jOJnP5q4B3aOpt9Y6SVaCEZBQSEZACAoMwAs+npIdtIGlzB4/b55Mnuescy78KTO2LEtr7XQ+T9NUBxmGmhRyJMgSFKwlE6r3yishb1UlyHBPjxNb7WfxBEsaz3eL1m3pfWlN1U/zWdtynk/tPJsZYQhjKSNSvUxS0s+o9z7UwQ3UGyIikoKrKjq6wbQbVqwOIm60L3iie7VOWB8xM48X9Glis8bDd9lM8P76eAnW7z22ntz7r/MY399JB77/dX604Xj510uRljvzDyYzP/Ry9CNsF0TiFZn2GML0PfdZRCS5BrYt/vJ3CjGApD9b7+hRhJFhbv3tu/t/+d2//v3f/+P/+X/9j7dv7yIAkFmqq6l7OFr43NsoRIi+pkmRnDRKMzQmYUx6R0CKP2asU4TGGrCQ1zxv3TRKAERUBSDE5XRehuG8243DMOz24263K0XSw9oRHRbq1Ju12kopIvSYLFEqknoyS8wj0m+aOCKWbhnup7nN83w8HnvvvS/WO7gLI9Y6VgEpEJSpzsPD6fXr1zzsboedu6taIBAZovVm6EjYRxtWb1oEhhyf5inhekE2ZaBNIflH4+E7UeGxyilfdu8fDI/18T8Yx08j9c++zg8ux98WIn4/3N+byj7e5j/wdj9yFriJzMAWxO7Z1g7YyKyIj12Ry0fahCgcALoGABQW8OjLTAiqqH159eabf/qnf/p//R//5b//j7//8quvl25IxQJFqlvzCEVsasvctcgwEK1OJgGADo5InoktOoMgolIQpkiwJ3Zq7Q6t3zWqm6fA5ybA6d4jIp0TW2u11mXpbdFpmoY0aycCt4iGiDxzrSVptYi4CVUHwNqG6uoR0UGRS0TMrZ/nNs/L3cPpdDqlrob3BhEEASKVIY1kCMDd5+N8nL+0EIUidZr2uwAytTmWcCTgIHSP1loCeFYy8bej5LsL8WUMR99RYo+I76l417vgfbODn5vBX6Lz6Qn9xKTovfeKJwdsthp5/MKSqJc3uPCp19oAEwe4fuP+LUleRAAhxhRXqTszwwDrCsVd++vXbz7//I9/9/f/1//7v/yX//GP//T7P/zx4Ty3HsNuIOGsQx1Izee2nObzfuRaCxFgkK3NbvJEegMyIKATkUgtoqig3gGAAPXS/kcEwNWm2Q2R0SNCTVcxptadzo2ZH47z7jgdDof9fr/b7Uoh7XN+OiIqRUtpF+1VREwrerO1xHT3szcuFRGXuT+cTg/3p/vT8Xxe0MPMwIOIhiqCgiBgBKsYO57P56/fffP63cNiwMPw6We/rrUSSWs9rA11ZMKlW/hpGIZNtH4lEa93YKYr346nH+nMfPdugW/nyr9UIMFPCPTv3lRPl/On+cLTh/38cH9vO9hKiUscX1bu1BHAbbV4ktLhJfuMuIhXUe4NrTVPt3dzbfbV11/9t//6X/7b//n/+Yd/+Lt//pf/eXc6PhznANJQtuDCJAQRjBQRy7Kcl7n34k4FATAEMIB0VYQEQyiIRIUZwSNqxU1wBp6kVR5xKecMKcLXhDupnmaomQ2zHJfhuDyc+vW1XbUYhiGsXz4vcxcRruVio06bkYn37DfajIbYLXyZ+8PDw/398Xw+924AwEhCzBUKlbFOtQgROYGIOND5eP788881vj41c5I6TM8//GgcRzJTN1YFZjdAj9T1xsvH3NwcnibZT5PdHwkvXMdVj3/EH33WX3xc3u5HHvM0vuHbH+G9WL/8/Fev7oFPu6CXb/Cynl3cGi5v+bQQfLrRrLkEkrv3pZ3P52+++vp//Pf/9r//7//Pv//7v/vDH39/PJ+lFmCyriSkbjWCEjgf4aDzsswzL0tVLXVIy9oAcHSOCNs60ARYuAJ7RCRhGTYxk8QGhpm7Y6b+xBFh6h7giWlxCA93iDAAo1nvz/3+3PcP81CnKnj57LTqSXUqghiSHlWQokvNurp7Z2jroefzOVP2tLksw1gHGaRUKbXKkMV9RRFpCvM8v379+u44P/TeHKarw38i/uyzz+o09rl3be4izKHee2dmcYe85RLTs64xjwqHsF2gPx9hT36l71vy/x2O74byD4X708f/wt5Ml/3uIodyEUm7ZOeXRQ4AieQyMcnV7tRnbe3Vq1ef//FP//B3/+M//+f//N//23999fY1gEstyKStn5aoA0aYo4c5ICCFqTb3c+Olz63JYdgJ5UbNiG6RZm2XiioQqQoxFgUAKRcDXk/vxdRoB9CIcHRAB8xxra2tFogAU3B3PM8PJx3vW63HaSwpmUZECIxMWbASERMxIwCEuVrLZKa7nU6neZ7NTFtvfQGAKizEQ+HdMAqhFCiMzGhmIgMRuPui/Xw+v7nzs39OMnz8q89ubp99+PKD/XQw6nPrQl5kcndrfb74fzAzM0UwIBJduv6PF/FnIsD/mlh/+tzvLuc/XgN8b7hfjkuW8d6zJNsU333Lp3TGpw+4hPWakMCjiO7lB9jcDzPTxVVmqOSz3H1ZlstrqpuZnU6nd+/eHY/H13cPp/uHL7744n/+0z//wz/8w+9/9y93x3siAGKgaKbuXis4BAl2XaaCzESOAKBgc1vm3gDAIUop4YoYjDw3cwywxixC6WqFyI86TUhxmmd3jVIQcek9UpofxcM0IDVYA1I9jxzAAxxCPdyhqZ6XI8I8TnkDC25UkotoFIIDAGMABGwqeR7Y5mVeThFRhRFREIdShsJDEUaoQlOtET7P51JXFPHclnmekYnIH472zTff/N0//P3VzfXt7e2vP/tVRIy1ZD90ZHZ3O88+VERMMfhpmi5jtbj4CKzq5E/09L4Tdk/r0b9+Uf/eALv8fDmxn/JGT+P7Rx4v773l05QDvg+7e5HQNc8ZzaMA6tObLEMcNpzM0xPqvR+Px/whd/HT6fTq1av0nXyVQf/16y+++OLrL7+6v3/nYVIE0M9z1wARpkpLczc3MKcOKADu6AGgEBqggLo1m5kJMaCKQWx+8YnI8ghPLCMLBkj6oiF3RLxMQ4UFUnljWywQkRLXhZg2IwGhmiuKL11XSbNtJ3msUxF4xdw4BQQYbO6CsYJtgJmHKvtpNxYZSinZ3wyFoP9vdW/W5EiSpAfqYe4OIM684sirqqa6mzMPzXma/07h6/KBQgqFMrs7Mtxp9nRWXnEiAojA5W6mqvug5g4HIjLrnJGmdVZ0HIDD3UxNTc/vQ0JmTIgxymw2m97fiUhZQazh9m56fn7+r+/eHR4eDqvBwe5eVZacCNFSEzNcT5JIkVqSrLIsu2XtgHqI8oFoX/AU7UFc/Le1Yx5+7sMTAL4q0A+Vev+CGzgzfd9FM0zu9nbp2Aq6q3fVXe4SBS6opyHq2KS6buqmq2daOPvWYjGbzSaTyXQ6nUwmFxcXnz9/Ho/H17c3McamSRqTiBBAWZZFUSxWczOPHyMBMpKYqkQFNHeJCaNYoxYNotvczAyYw4OgIJIy5ZyYmndVB0YA9lSWm1UUGaCRNi82pDIhodbJQEHNIAECGCsJetgOAUABkoIINMkABHPOdCNOTQiIwO0/n8Kg4hU4ZeBhNRhWPNoZ7u0OiKAsAzmulJlPLzANBjuzxWoyvb8ZT5Lgzs5OY4vJTD+dXYRyMCyHB3v7w7/5fjgYIKqmFDAE4qTSNA2ZVlXl6H2+jl2Z0NpvdWXny/dVQfy65H3dy/zRYb28ZN98+NI99Ac8OIu67wPQ2tO0PvwktTXSrT3n0yASiYjQ/8fdXiczMGxiqpscmtCWzXkymVxfX9/c3FxfX9/e3o7H49vb2/v7+8ViMZ/PPRQjIt5/fbecazIzC0jeRd84iwtIWYaA0ESpYzKvHTZ00mcjFENFbABqg1qxQRYMTOaA1USklgCUicGSKjEjc2DOycUQqsIN5CWqgpi5IlRDBAQNEaIqiykLKSGDNMkJndUIC0ACU4I6gtdlITmAkpmCU9OgU5qjzz4UAYigMAiBSubhqNrfG44Gg8GwHAwCkjkkKgCYAhJRKAlLLoaren43nU/voxAVoSpLMJutlnF8Pfn48fPnN+evT18/OQiDkmKM3ukKJogWEADUNIkaqpE5Oodnl9CjbJ00uPSvq7IQIBPObAa58ZH8OvwKrf9QpvsmxkOx3hLxh9tvQ7tvXaV7RRea3TLdhsNhp6fdYnFaDBEBy/CldR3v7u6urq5ub2/PLi9ubm5ubm4mk8nd3Z2LuEu5M65kzqD2U4pQRYsSNRkQmKqJaOaLDEyI2SxSQ0KmlpMNTADMoDFcKCwVV4K15kr3ghADl8WAiwJSFPHYiBEBh5wOzVTGTOjNVoh1XYtIIcoERQCvTRAlVRNjYSqC1gSJOIqmpN6gRQZgOV5FiEBsaGYUmMwEVBCAAJggEIRAI8LhcFhVRVWGUVVVJVUFVoXTK0gyFVMkDlU1HI44lIt5fTOeTu9XMQEVRRNNjAihafTubvb508W//H9/Pnp2NCpH+zu7jEFSrmxzoqikGmMk6Vh3chjtoSLMv3mgTLOV3/24+Ypfb9DDpmrvOhC25FvbJriH0t+/z60RXNq2HhIRRaSfIl1fJSAgAAMTMxfMrAIxxlVdpyTL5fL+fj4ejz99+vTnP//508ezz2cf7+/v5/O5V5t4fCbGCL00U/856yaJCKgnaAmBAzOgmkm9aoyYsRwUtqwbTcZFQDBHxEsGQNxAWAne1+kJBKFSLCVNqMpMRcUlIsRVjLFZqaqkWIMFB7tjQyKvqQoUmEKNiHVdM4oqJAqVmphKMjEQQyEQ4zIUKUnd6GrZaDK1rq0CwNryegAwQ816kQ0YoAAoA5YhjCo8PNzZHQ28lJ7ZCoTAxEzRFAwRAnMYDvbKaiQiV9eTy6vJqpbAAbhqaksJDNnUlot4dTX+l3/538/2n5ZU/P7bv9nb26sCi2lKyaI4qgwiMgeRiF5jb+5JF9hrMIfeZshQlT3zYFP9btjTP8W8/inDHqRXO4Huh7C39sCjH9r/ZWZgc8u1L9w5jLgp8Wa2uFtQO1Shruv5fH5/N7+5uZ1MJh8/fv7w4cPFxcX4+vby8vL29nZZr+q67nsC5KgsiIhEnI3TnM408IpJICQnmkyiqgBGjGasGfDCAobk2BIICChiAkjEEXEpdl83jaIgQ/CmBjFSBUK0kpgKYMSWLkYsKjKnlIgNOBRFgUwUyhDCalXrauZHlnfQJdAoSmrERACBOBIjRrRAGBu2MgSnPpVkYpoxdQAMEhEExoKgKnA4KEeDoizLnVIPdsvhsEITxLYQQ72kBgoulDgUVVmMVPB2OhtfTya3s6ZWxIK4XDVqwIRlMSjBJDZ6dXn75z//ZcDVMAy+ef2m2CvR9UhdU4qhLKuqKorCw6ApreMNmUr2J+Cpb0gVtb/Bzb/+KtM9Xwd7JSfwQOj7H7cl61+6/+BQjO6lWet3umrvQgr9zyCClJrlsp7P54vFYjq9v7i4uL66+fTp82w2u7oaX19fz2fLGONyuVwul0CoLaWjthWI3d7twmHQqRPLIHsiYGaoQEzMVNd1KAIi1jE1MSEWhRd5g+iaqAkNqRZZ1DJb1U92hqMicAgBE0ADORuQmHkwGHjbW4zRzMDZjgAYyHLosAwhlGUVKbkHgpjQxElyxRTzi03JSmaqIIQwVFiugldrrTBBFHGsFzAzYKSqDIOSdwZhdzgc7QwGZRFgXpaBUQGxLDJpfVPXgAzEZckcilBUyLycr27Gk9m8ni1XTROFKAhIct4cQsQUrZFmOk0fP3wOhrs7OwGDnRyMRiMn/RORwszMUhO58IhTzrWtC1dbUpNuXbRXzWK2xo/aEO4H3/8m41FRznf1c5CzO3kLZZn5e+u6y35zUQQRMUNVcDo4AE0pzedzEbm/v79ux8XFxeXl5e30/vz8fLlceQJcvOJPDAAYqSwHXbmpKliuoduuFG2fSgABEfLxbyYASRMUHM3ADJkKDCLe12a1VGTGzAUgCjIgNrKCxaJeTetFqEaiMAwwoGCWEFh4BIGIqSjUC2JNIpqqNOhcwaFkKgyMilASJtprYqrrGqlRhBIIRQuFZN5FikF0UKJCUAVVjSNuJNW1Vo02USWntBDRCrZBYaOK94bVaMjDAZYMVRh49jaEQFyAATkoqwEToZOZjAZLs7PZ3efZ/Q8Xk2WSBogCGwmU0NQNMkRJXAZJhog391P52GAJQinK61evXg13dqgsVLVJiUIQ06Dm2YCiKCgUUQxVy7KEDqnBK4wAvNOKiJxxvi+IABtavO9T/tzx0HrZinh2EtIaAj8jItT9Msxms7aPzrmTBgDgtrXHxefz+f39/WIxm8/nd3d3Hz9+dDfUgy3ugM6XNZFDrxhRwJwrzVrc78+Nh74u+fVj47BrZyelVFuaTqfDYCUKDEIxDFoGBAITRXBCUSYmLBnRhE2y5w0AoJqaiBRySL4ahCBFyNRS9UBSUqdK8Gxrd3IrECIaVDHGRb1a1TFKUgHLgKfCCEXgYRGGZTEoqXLCElkCKKA3hhtCvjNE5KLAojSi1Wp1v2puJtP7u9myXsUoyfL28ho8ZEopuTNaBELE+Xz+ww8/mFlazaLI27dvnzx5wsxesp9UBoOcG/F24c6ksSTurHdS44IlWbx+Xjjylw3bPE/6v/m6rP/oCKO93abxtgAWkWVdN01zf38/nU7v7u4mk4mHDieTyWR6c3d3N725ret6sVgsl8sMYo4wGAxUFTHLtCavFyBE9DaOzkaCtrGge7CtTfwTn6RzjLKsixqSb62oIkmn07uCLaCSDofFjlWAFNAITMDQkIiAuCiYIbFIZDTHEFUTUUUVLgpGoNLJ6YuqtCgpJY1eKmmQDMCIAhMFNSPiEALQIKVUx2bVpCgpRRFTM5WU0DQQBMKKKTAwIqioYRsHNDPBUBbEREQhIDOEYqUwny+vbqdX1+PpbL6KIgmUgMxEMswNE7mDVBShKAIFjFGub8bL5RLismkan/n9/X1nVSEKXWzNzEJKiOhk7IHyvfT54FtjghC3F+i3EvQfDajDprhvfe7XnY1uhMViEWNkLmJc3N7ezu4Xi8Xi5uZ2PB5fX19fXV1NJreTycTD5KvVajGbQbfjQUz7PUqQOeTMU4mh83SdZqzbl52Ib51fP3deiAgBQU1RUQERDUxAVXS2XFR3VJIF1J1BMagKLpgLZmXIlbBYssPDGKIFGogICUQxAgXPHqsCIGNghsBQWiliYo4/B0mUKISqJCJTRKayLAGDmSXTJBZjXDb1qo6SGhFBEzRjNAYnvBEQMGQKDEZmZIpFUVRVVRQlhaCAtWhT15O7+4ur8c30blUnA7fqyeE9zMDzxkAkIE0yYqiKMoSQ6nQ/n717/0NSqWPTpPjmzZudnZ29vYPhcOgT6IUGzohYhhDaWqa+jWJmLejfj3uxv9XYUmdbY0uQoCc8X7+94EWni8Xi9vb2w/tP4/F4MpmOx+PpdHpzczOdTlerVdPU7si7nnO728xMsevDrOvITBy8m4H7Rp7b6F5T0O3Oribnp/g6D18JXVEDOseFgPhxjA4t09RpxnNGCaAD7zba3dkpKi6AwMBETJMYMTARMoeCJaaEidmRJV3axYQBFXKEnzEYmymY89cxc1kFpmBmzByqwiORakFEVhE4aMGaUkEYzIxMyYw8T+CQBMqBS+TQJFMBDoPBcFSWpQItVvVstbyeTC7GN9e309k8KYARGBAQC5iC+Y43ompQiEgTV6aRyarARhhjur69iSqLeiVgUezk5KQoKufUFpFcGMclAhMGBFZL/UnWDdPiEanaErvfZDx61D/U9A8l5EdH+E//6T/nNNDt3WQyqetmuVx6PsjNlS4K6yn2pmmgJ7XQit1gNPC4inemtQhCax9/Hcc165tlW6F9+0KiGHo7p4vteOjIAFTMo0mGREwIpqJNlPvFMqAWgQiBKHAoi0FAAlA0Tc6YCsQBoWAkNCQrIDezpqhJZRXBzFDUjLRtS8+JVsLgbeOoSMgMBZp4uY2k2KTY1JZSQVZWGEJBaGjAaKBG7oSrmSGHAoDqaEmAwqAsK+Ii1nFeN1e307Orm6ub6d0iNgrEIIAAqKpIbABAmEMlDsYGRqZNjIje8I0a4f5u3tSfwKip0+3tbV3Xy7o+PDwkIlBse/kycyAG7Kwr2BC7jeypwiMmzW8i9H1p3tpUWzq+e0s/1vf1Ef6v//JfZrPZdHrvldbe7lWvMpUpInoiHAE9aQoZchHM2mc2Q6Dgp14XkGkrZ/p4FX2J77zVhxrdHvPKHx39C4IbVISKWAAbaTJdrhqQBABqhsQYqsA4KEPgkhDNSBEpIAMhArd5BgJERA2aVADLDvoLQbRNNVLXogQJVIiZEdDAJIpIbJIjxCiYWwpVFRgheMrdhLz4J0c/qElGCZIRcQXATYL7ZXM1uft0Of58eX07a5oESgDEqj7tCGCMCIhqJtIkiWYaQgic8We82jcgAMBsMX//8cNsMf/4+dP19fXr16/fvv324OBgf39/ZzA0MxHJwejt9L83haxjaO2ir5fg4cL9VuNRKe/Leqc3f6LEh//xP/4nrkGOnJZoXefo9boxRQNPyuRaImIqilzj6r/PnGG4fiuA854GbYsTe+FIffTmth7jJ05Kp+99X4IRMAKoKERJKYnZTAGLahQGi2HJSIEGAZHQEnpJI6kD5xMRgjqvdQhcWMCwk8NKGjPBEWFukGCvrxJTNVfagKYNmBo0oCvQmhEDc1XCsACPgRAgWgAAImIkwKJJqihCWFFpXNTR6hhvZvPxdHZ5MxnfNvMEGACQxLhlAUQidNWuLWk4AYbAgTE1UVQBAjMTGDODoLte4/F4Pl9eXo/H49vXr1+/fv368PBwlOKoGgBAWZaGZADUp5DPs/y4LHZL8BMX6+eOvkg8lPgtKf9RscGXr/ay/KnfdAfV6YfXFi1wDy96i7nKOkJnV7fbreltEWyOS3Y/9h9sa+N2v+weLNfWto2w0FPw3VcCQ7KSCVUZhdBIJTDs74z29/ffvjh8/frl8dGLiqEgrRirgBUjaoMSC6aqYJVY1zUalGUBxTNVFY0iEtXLhjNtPJBHnGI+W8BERKlp87WqZkQ0Go12dnZ2dnaYKKW0Wq0AYFhWRVGZWZKwWK2iYCh3jMtFrdfj6fn1zb+++/j57Pz8er5KYATGqBjEIDGaYxGDlxlnG2O5XCIiIxJBEcgFHRGDJp8Zj5Uxc1WURVHs7+8fHR29ff3mu++++5u/+f7ly5dPnjzZ2dkByjRvbtl3ta7D4dB5lf3o8LxhjHEwGPTP2K48th9/64+Hv3/0JO90Yp7JzWjMLz5GgqqqdBfyiivqhVc9IttJNssjsErqTUtk0Eav8hW2nuHfyalHQCMzx6gOCCJoJraIgMvmcnJnRbWMuj+qDvdG+zuDAkkQmEoAiGaYgLkcjgoCRLI6Q+ARtBQgjuroKPWqSYSdWkY1qVICY2anWAKAEMJwOKzKQiUhBGbe2dnxUHyTUkppVddAgYpylWQ+n90v0sXt5Pz6dnw/u1s1tTjHLxiwYhC/GUemxrwG3do4JbAjo6BlfezgeV2uAxH9KFitVovF4v5udnM7OTu/OD46evny5fHx8fOj54eHhwcHB97Q7fFKAJjP55568APf2jKT1WqFPQSKfCdfkHV47Ez4UZP1NxxBUtdMzZ2kmm0Ja+ZU6r7vTXL3G18VIMBexo0ejV79G8s9GVpSAIQAIBTAMELSOjYKKvG+lpvp7MXTg6jPvTaGi8I0IgJInVIalAUPKgBLItlURaSAAAgtRUdbKZ56saakqo1lVaqqxFgVpWNvzOdzYqmq4XA4JAp1XcdVitEaheFgaFwspouz68nVzf3FeHp+Mb6Z3E3nsTEwBkAWYAU0YDUvpjcEdNMtqyW0lpVA0bhdF+tUe/9oVVVCbm4ni/ny/v7+4uJib2/v1atX33zzzYvjo5OTk9evXx8dHe3t7VFgMgU1ZvZYJQB4pYMre3fwrNcS9fUl3rI9fvT1v+0IrpkAnfLBWlElUWi987X5AtAB0RAAIGzVLRCAKYIZUAtB0D3Gv9HzdGps607EBAEFAZARwQxqsWgCJrNaZotmFTO0otk+UhhwCATIaJSUWSkgIqCKdvDc7pe0sSEvTCUmI/SKJSVQJUUkC+rOH4aiQGI1EE9LGIpxSrCspRYDCsPRyLhYNnpzN/90cXV2Ob26vRvf3i9WsU6gCMRBjJNPPmYmDnTyj9wWrz4P6HEaQwCgXLKV1ZaLeF4FQwCsm1rEFovlYrUc396EED6dff7hw/s3b968fv367u5uPp8fHR2NRqOiDGVZVoEJcLlcepyeMn0Dexqx09NbFumjY8vK3foTPoi199+VF/2XylLo7HUAgIxDtE6nAcDmgbl5c0CA+igcq7bA6n1novv6m55fisZ9NBDvL1JDBlRz9DACJjMTgGVSShbTUhEBuWlSjDGJHu5UgwKHRVlQoWCraAUDc2DecCoUDMzAAE17KwGq3uCHhoSGjo8thqzgwhbCACgoUBM1JV01BliEUBbDncnd4vL69vPF+OxycnY9mcyWyyZFI0VFDsaFJ2YRSDHDV5ujtpt1K48ADIaG7Fg6+c6cEKQdCu6CE5GjuKkqBlakRvTq5vZuvvh8cf7uw/t3H96/efnq9PT06Ojo6Ojo6bMnx8fHRrQ+HIiKovDKyv6ydvvqK0v8JUHvf7P19bcSmICYTTrTzHDymB/wwETsfjSyLPHUXcfzEYoZhqAv6/82Qx9gVmLrSmeHjdvwtIICUQKbr9LlzaSuHZWxkaNnBztVURRlCCopSVQABggDBtfLqp2L3F+M3PTU/QlQ28ZdMmiShwoddYfVSJKYMhfu4XEd7fr29v3ni8+XN1e308l0PotJjakIQGrIBqQgBmRO3epmQ1fUYmIAZECO6I3bUXN1ykogD7Xm+BiTqiKRw3o6kU5KabFY1PWyaZrpdPrx48fnz5+/Ojl9+/bt6enp5eWl2/TDamBm3lyf60k3G0R+VDS/pN37b/yJB8XPHcEP6ZywcJpbfNw8yCJumz+Cnwnb7/DT1uuxfrEf/dNHZ9J0lO2IbZwOgMykjRx7rzagNZJkXsdVHZvVfD43TfHZk6IoiKiioqwCebOnriAXjZiYKKj01CUispnlClAxM2M2MUQjIGPM3eHsUUc2Q1OmUDCH5aK+v7+/ubt7/+Hsh7PLq8ni9m4xr0WAidk4gIoYGpgaqve2Wq4u96RSj6FA6UtGYy9Ehr3m1HZRSFViStCSl6xWTUqTu7u7y8vLs7OzDx8+/PDDDy9evHj56vTk5OS77747fnE0GAzKsqyqitbwWOsC9J+o3R6V476O31Irv8nYYM3+sbvJThvAT+JR+K2Nlp85WiMbAMTaOixEMGNgU1G1mGKUWK/mq9m91MvV/Bg01Qe7T/Z2Dvd3CSGmJLGBdQR6vQBriScy51Fy80bR5YYZEcjQ/NznUCByEhM15sKA7hfLT+dn//ruw/nV9eV4cb+CWQQxoIq5qERBcrm0fyYDgIDxWtFkGx02dQ2ZkgEZ5YxY655ii8Ys+ZqemDPJRXHqzqikJGIpedwoLZfL+8n07OzsT//7X54+ffrdd9+9ffv2xbPnL1++PD09HY1GBwcH2sFr9hLt+oV69Ici8TA+szXJv1IQNj7r6Yt96NXi/Oz3b0YaIUdmuj2aTw6GdawqpSSauh/7Xg5A5umyNohmZtLOIAHkZnAzr+EBAOQNrebQowCAgQFADZ3tqOsUDMAmCRELpxVLEaUhTU8Pd46f7z9/uvfy+Nnzp/vPDneePj1UiWpj8JQQFwCkAqpGBmYIiiBq5ho4L3kDUOX6fnJAsaLgsiyTHwBqIlZHWczrz58vf3j/8f/5eLNcrRbLuEoWDRIRhgEWlQGtoiYRt9NcXkMIRbNERLK2jB4AwFAtSUNgjMQBETGnb8GaH2sr8mnpnVeMvUEEDhFVVVVR8MHBwfHx8atXr968ff3tt98eHx8fPz+uqmowGDhGIvQEF1usOIAukKVI67Ol++j+/fSPCzNz7P/+cfr1x/lSq3i+pcNnu1tWV/+mf/TqD9T84/RuiMgtNKSa9NE7viruTvpuHRtRaNNMbY0xUOjV5Bhk+goAyIFRMoSOxhoR2VtIQRmJEVASagygw4qrQFXQZwc7pycv3rw6fnn6YmdnZ3dn1a4ZMRIAiogl0WSIyIigJiLqTYaiUJatw4AYCkcNcVZhBRDT+ay+uLr6dHb18cP5+fnF+VxiglrAAIRJkI1K4yImjYqAyFwAgMRc01Fp45OZM7sAZkoGask5mZy0td0S8HVx76StJ38t1keWQu062lST5w2ePHny8uXLb7/99vT09Oj5ixcvXnRZqqIozMyZf7aqqvJ1oO/irzVs9ynWd4R64t6/Z/iyhfN1cQ8P9xb0pLy/U7cm6CcO7Akfgnrb5pasb7yetiw2F+MO0kwBvKc2u57dDZsZwlr0NXf0CQCSrTWWoRoYKCgoGDIihQLAFk0zmy1BYDJdrpIpslL5zTcH3HAIRRHYzBAQQclIEKkQMnDOe9OoJmgGBDHWKhDKKlBhZmqYgFerhssiiS7rdHkz+dNfPv3w7uP19eR+DlaCITCDIBEGBdCcm1QDJAyEBkaKyICmluWY8oEF/QXyCYFcO6+IAP51e3TCbQDWtlCyp2KBMlmPmVoyy0yaIQQgVoRFvVqcn306P/u//+n/HQwGr09f/+53v/vjH//4/fffv3z58unTp1VVAbGYEefmEa/CiCIAgLDWdP3N0K+Q7bsBj5jUv8IV3GbvgAf75hGJ7IoZey9s3+XlB+1iZFM//1UMuN3oD28lW0G4taM8Wuy9B0xEDG6MgiUFAFPvdDNENFzXluUpzQxNZi6OgIqG6GW0YACKjGhoClRoAOa0THo+vp+t0oeL28vp8puTwZMnT54dHhaBVBNqclrKkoOkmFIdY5QmqiV/LsaKGIdVSeUgJuBqGAZD4vJ+uRpP769ubj6fXb17f3Z5NVlFwAKKUJopqIGSmAmQthC9pKCqGhMiOt8TAAbrYEzbmTVQzXU+4A/TZQkfY5LZ+rEvPWYGKG2I38ioe73nVr2t3rv4YxTV1V/+8pe7u7uzs7Pj4+OTkxMP2x8cHOzs7AyHw8FgQG3zK+eaoQBtuUF3A30138U6XdL8YGzra9tkFv5CHJuwJXmdxPd//6jEdzQ9D5W9Z/zaV9L2hD52RKxh4EHbyPKG+vfiQyJAQkpARF5qC73reLwXe6/PG87ZO3K6WCCznIIZqpl5bBIRAyKWKmmeYH47P7+ZzWqbTQ9OT2OU4nBvNAhUUEFgatHEUlPHehljdNPKxT1wiElwFUgpYVDFJDSL+ml89/7z2Q+fPl2Pp5PpbKWkTEQhxRoAFFBUxDkEKKw53iWJI0i1xgBZl+hyX7OtUMy7HcjjNp5P3QrSPCbrAOvDVnvAoFs6uCxLb17z4KP3+4nIMtl8WV+Nb/d++HB4eHhycuKBy2fPnp2enp6eng6HQ2YuiEyhjs2A14kkAHDvWVUDh7XYdxx1iLiZ9+hu7GeZGN0IW4L4cPSfH2BNRrX16s23Z/YARARUhLWScFtk613YrzrFHOf2BO2j11cks2zSbW3EB09h4B50hnPEaOJi6SymhKBgosCIYBQNCIuyDCCaYn01XZqsJvO4WMqb06Oj5wdPdysuqAgUlzO3TZmZvFbM0DCzWCa1YGihqAVux5Oz8fjdx8/vPn0+v7xaNWJAUFSm2CShaEgATEZOGNjVVysYIBgjo1Nkmroawc0JVDAF65p/tWPMbm2bjbnYnKsNq8bMHKqytSIQ/OQEM1ssl15kFgIjBUASx+0QbZocxplOp+/evfvHf/zH3d3dP/7xj998883333//4sWL/f39/f39wWAAAEUJLewFICK3kQbVTBZkZojGnMPhjqQP62qUDvPsl4wNjMhuYC9Y/vCbHxsZNhHJ3MYG1L5JAz12p94p0V3ZH8y61WlNTAQnFtOcw8pGUbvQW2aebBIneo7d5d6X19p7JSBDQ2ZgjnWDCNKogSDwzd08NTCv02JZz2bz+exZc/T02cHObsVEIXBlBaJKVEEQRiAKu8Nd4gpCGaGcC97M5u/Prt5fXv/r+w+XN7fT2QoYilAxs5olQEbw1lQ1l1DK8U4zRGJAr4whBLfdofV5ENdHsZmXJbcTib0ZbWfloWqHB26fO0XrtUbtCl0Hg4GTjphZSom5QCTmQlFFJKktVrXbLUktiv7X//bf/+mf/9ezZ8/ckf3222+/++67Fy9elHullx7YZgq2s2Fss1bcyXPWxlsLufHLzPcA2h6cuXJ3PVHQzUgn6A/tlu3feKGM5pXLEeK1BwkACuoncu+92FM9PXFvj2nI2zpn6cEAgRUBCUG6xzbEDLCL3jnRu6t8ihgQM3oCXhF7hU1NjFVVcRGyGBmWo0Gc6ypGuV9J0hjjYnG/nM/j6fPnT/f2hgMkQzIxEoWoRhhCKIUrrgZ1ouvp/eXt/MPVzbvzy4vb6f1yuWwaRaDM0O1yJmoASKqmfla1rg22iH+AgIDsJZi4NnMeHWaGCI7nigBIuXLJbPt9a73ejtze0JZIETq7D6qaIqzchQhMGMiBghHBMkeDtiDP0Pa/isjV1dWnT5+ePn366dOns7Oz8/Pzly9fvjk6ePLkyeHhYVVVGTqhLUbw29AWiSinC3jDAOmCNh1z488a62v15W9zuz8+rfCIrANkpe4aWT0ODmvyza6YXn290TbWz1Wan+MeqnWTrdvrkH1hAqJcdeU7qL1AS1dtALkuvNML/n8FhFzQ4+6FZUWPBEkiEhp47T80qR6MKhCum7q5n9XNYjGf1vNZalar+unx86f7uyPCYlHPYlKDIqk1DUhh89jcTOcfL8fvz8d/+Xh+eXsXEYxDUVRUmKpaEpXabbJyMMzIBpatEDMDVWz5TdGAPaPq9wvdFrXNAYhONt9bRFsf1FuL1Rnr0NOdItKi4nSvz2lhESMiBHbtjojkiAmE0Kuk6C7uYIzOzulQz2dnZ7u7u9+cPPnd7353cnKyu7v7/PlzrzQejUYhhKZp3Amez+cAUJZlSgmtJWJoOS8eGvEbVtljIcvOMNlm79iS7y+J+xcmscNLMmzXDjGHatDtUQDYlO/uRzIAQIXgDcGw9lgRDA1d2xsYqSscT4hYqyk7UxUNnHYmJ7x0HSYCdyvQFHruvQEAI4GpqXkDC+WsP3AoDVQbXUbR6TLFRkSm9/P5Mj492N/d2eEwGlQlENZ1rOv6/cV0vlidXY0/nl+dXdxc3a1WAlxhNQzMGJBSskbFEiBaSWQIpuhOc1sv7ZOYN2KeUUSfIlmbH1/0tboF7l72Jcesv8Ttux5NuZD3PPQsECQyIlJay1xf3KvhsLvCsq7PLi4ur6+Z+c8D+qd//l8vXrw4PT39/e9///r16+fPnz979mw4HAJSKAoGqNRSSlG0iakidhGnlv+nL+Jbevmhvt4aj5PVfEXoc4C798eNeUdtf3STvQuWQ682+5FBBtlMVPQsqG9eb6IAQstBg5Y3JsOrkKh0wc5skCEaGPlXWHs5YGsmlnzaWPtfhlbwQCUgGqCakYgYIiBhUYLGOqbxncTm8vbu/vZu9vRg/+Tk5Pnzo93dQYHVMuntXf3x+mY8mV5d344ns+kyItOwDIJuwAAimiQwYK/rAkuGADnO1npjuSEYIXum3Sp4PTu0Rks3/FRE9J0O+oXAxcNDu7+yvVNi7Ue137fHZJvE6ZVGtqpk7VQgACyXy423dSCkdVqtVufn558/f764uHjx4sXR0dHJyYlbOIeHh6PRyAtyzMy/WuvCeiTTb6CrTus+ZXOTr593fb4/FPeHOrtT5PlHAPelADvdjI9oGjJwyPf+XmiPBAQy65sU0OVNu0/MM4hgwGBABH0V4n2i1rOTukO8cxfcovIyKshIfI/79GhrbPvWcBKJycyiNQVxWYRBNYCijqvldGXLZrmor69vF9OVTBfp8PDpaDRarlbX15N/fvdxcns3X64UmMthWVRAuGyWdb1sVFUBEUoGKsgJijXX5YFt4NFhF5l17Q4PTur+XLV6Li+T16bmR293erd6Pln9K0Br+WhGswenBe1HQBCQkJjXUXMRccCdtWPcc/C6hwFzDCvwWOp8tqhXDdF8dj+/urweDofPnz8/Pj4+PT199erVycnJ06dPnz9/PhwOiagsS0UxAEMQFTENkNW867XuadwozuK4qen7EvWIdn9o/Wz/FQ0M3cftLLy+vumqUxH7cXHsfzDAOgfStb9b61F5VMWVLmQgZnQ0j9a/3DijrWO/7QISiAY5q/UQg7x9rvbtWUg098X5r5xfD1DVRCkBMVfKFtOyrmFR10z15d3i4/lkd3d3OBzGGG9ubi7v7xeL2gCKokTGgoShBd4xdbIPIXQyQFWUzjWE7ogBM/EgoDuM1uYNfMe26qoXlnnUiWrV7qO2+6Pri5ibPzYnbAP1rWvsQEQI0K9u79sYZVl2qt2VlMOdD6vSNfR8ubiZ3IpY9cO70Wh0dHT05s2b09PTk5OTb7/91sOXT548IcbMz5xdfHuUeaDTj554fvho+QGfPtvrP0xfkfdnpPsluTbR1gnoGYgeEAdSIkAyyvgVZXclMwNFgBx2wBzkArJ1jF2ZzSy1KpyZDR1Rw6xt1MW2BMrMBJtuvbOt1PJce7V9zuO25m8rB9sKoJ0B6L8GEROYJTFQImIE02RJTFNRBNDESEWgsgwhBGnifD6vsSDiUBZMmQwMmBAzPrGZJRVJpmoeXfR0bL63dXu7OUkEABBkWAfybqi2hGuN1qzJzAqmXpCgewRQo0ef9OHYqtwiog7rvTc/a4vFtaxnWzux6faVdqAVPe5oVUVZdaiU3bvMbDAY7O3tlWU5Go283NL1/ffff+8sze6q9pcPelK+fkZT3Ihjbriwoft5SxS+NLCfw2gdq94f1eUqHziI3YN1essMUdenXqf18+oSacvziGsvU1WNCJh94iQiBqT+9cU0XxAVjHxLooEAcO5o81t0y3gD5GztLiObuSCiM6sjSCIUERUAAsSSSvC8H4eQJDUxNqKIdYpRBLRgCgVQqYjAQZKkumbGalACEiKQYQJVMwAyJDZoneh8551OzGq1izcjGTgPVQ6qZNhNhEBM1DlL6xPP2uPyS+L+ULu5GQjZ51m/sS358vYB65apU67Y40mGnnHfl1EiUuOoJqDMTJxB5VNKyybWtxNHahlPpp/OL07Ozj+dX1xfXx8dHb18+fLw8HA4HHpDArQGVVtrnblKRQRMqccL3df9sGXMYG90L9p6Qyfu1gZ3+xOH2c7s/SPy9jFtsRPUuxXWpTXga9zehLmn6M5ie3lVFYdq8mgUImhwYDMwAwXyChNpo3W8dkZho9KA2gANQBsNyt4IY/DywxY1BMGCgSJyCKwASA6BKR5sCmXhs+5HHSCWA1wmjFFWqxlhGAwGVVWFQCGEGGsvgTFEo4CAqigKwR9cW///Ue3Tk9W+3sqHe9agnfmCZoaevEPTnvQ/lPWHEt//futPrShvgAV10J/d1623d8PvuSiKpskHssMc+GX9BX4UOOj058+f//SnP/359OTt27d/93d/9+233x4dHR0cHHRmku/2jsU2f7ptEAhsGSz45Okubo7+7XZz1J0arcv4sD5eXbsgGpHnAxHREMr17LSNQN7LXHDJzGDEkIvmmiYuJJJBVRaBFNE8GXE3nxmQEUP7kGXBIQRNzSoU3UY3yyqfiLtiB8ae3IBim5PPk9L5D92ku0NC6L2hZgMAAHNYGwVU7x7q1q8VmvXkqiqAMjOHPFuqCm0gz0FkfRo6Qe9bIP7rjn4Zsy5AN2ZCyPMZY2yalZkRIztbbJvjs4344wPt/5w1wwAAB4RJREFU3osKPBzYC7B08tBKhd+J12x1b1iLwdftgvbTY1+c+p/VvaSrJyOi0c7e7u7u06dPX79+/f33333z9u3x8fGT/b2Dg4NQcLOqRaSul44Cu7Ozk5J6RYNvA094eWMu/Ias2QAARmv3M3+/VkXdqxCREFU1pSZGNLOCCi+iIMIKCzXxLBUCIJiBMkItMaVIXJRlWZTsYIuhLOtcbWFmRobgoOzISR3asx+L+Rl8Dz4YHFXHE/yW3YzWudxcs/UB2llHXnfSKph2Wh5EsToL5FFxWQtcbw63VPVjb3wsXPZXM/rHV//31hv+V0efHo/H4/H49nY8vr5++/bt8fGLZ4dPnj1/erC3PxgMioIlpvbYZ2Z2TChoQ21d6ds2jfCvGBslA+ZeKXq0YROQG83UiEiTpBTN/CgIHAKHEAhVIoMxFSYJIUkUM/FmGAo2qAoialaLlFLBgRA82oyI4OUBakba3dPPGpv70gCB/HTOHIya3aHeerSaqe3H1p5q7SXRoFdM67eGbcQpezCbEoBtRAXs8W3w83TqX8/YPlv88Mkuijn2qJmRgQMtq9R1fXd3N5vNZrO766urjx8/Hh+/+Nvf/2E2O/3m7RuvR1iZaZK6rouicmAfbx7v7Cj/sADwyGnySwfBeoGxPfAsh5X9B1AVdWsezCgHekTEVBMiFkWJRCapCCgqmmJTmwEQASOgJWxFX2JiUyoqRCI2I0YPYZtpSrT9ONpT8+tQ6fo3XyiAo1wN4eKlZo6pkS1CXDcl9rLo6PAcXfnHRqiuf/FOZ/dtBuv/dW2GYRvU7q6jsPnKB+OvUsHTpjpff+PORg62GoKYaopUhAAZfnaxWH38+HE8Hr9/v/vp/YdXr179/X/849/+7d9+//33IYTlfDGfz+uYdgmLouAiiIh4/rx1Xje0+8+R+A3p2XgadHsVEIOHH8w6WwDMDESTpKoqc8mFZpclO6x1RFAVKIjNRBUkQVGBAiCDiC7md1VVgSZya0cSAqm2dZIAiExI+tNW2nCzSWXtMOfno44vXrOsQ95TBl684xwvAB55A1TTzm/zsvuHd7KmwcCcFei5U1mu8/e5grMzEh/kydv90DMjYQMJ6/+sgT24BFVtJBGRu2QiUteZPSmu6ouLi/OLs3fv3v3DP/zDq1enjgtyP1900JadXqctcf91qr2/YQjamuw2DNpOfZcI8AYlMmZkJhBNyY0EJfJsKBDB3m5JAGgwXy6Hg5FSkQzuZ/OmSaSCBEgQCJdJRJqUTAQQIQQOAYhLazn9EMDwS5sT4IHEr5/FAEHZOgRWVU3gKTBjBO+gW08BWvYvrYsxI9g6LdIRI26Jdc/W/4J2b79u2+5mGTVq669/zUOB+sLWP/Sy4QHQKQADMxEFbUA9CGMmTKSqZ2dnIYTp3eR+erdarf7whz/8/vffn5ycHB4empmntDo+yS5e9Ju6quuHYDPIuEaGBuKmLxIgIDMjWWqiYEQCVBABYqgqHg2Gu0MMBQfi7968Hlalql5f34SiQiqi4M1kOlssiahpmtVizsxxpQkQUlQ/3lGIA4Kuu60AvwCs1w3PSLflaHloPllNQMUkZewDr4hiY2bcsqpR2zY80ySeLvUZd2sHHosGftl2732PnQbpnIsNOq5Oi/0Cd/zfeXxJsVqb+rXMZ0p9RL6Yamki5GwuqOqyXg20vBnf1svVZDK5vr6u65qIiIKH5zu93qoehM52/8p9fGE8FmEAhnUNBblzhiSgqCZE4IC8FpCMEExVUQEJypKGo+pw/2Bvb29nYFVRjgbl3/3hP+zv7DRN88MP78XYgGPS4XC4rBtEvLu7mzARmDLEGAumpo5RlYiJckSl/zytxGvXXPKgZK2vIHungWZxN4mmaoZIgQAwhDZ+uJ3R8CUzyeCbvpD9gPRXBj4wfR5o9w1IusdXzWgbjvyveGypAA+qeBjRpbazbRiJiEST97kOBgNmBsLz8/OUknu0f//3f++g9QDg1+lf/LfU7u1+CpgBRhAAuz7jrrfSQM2UEAaDMhDs7Ozs7o52Rzuj0UhVh0UCkdgsd0dVWfDsfnl7M54vlgrBgFe1RDEiKpgO9/fMjAcoIjHKqqlXy7ppmkY0ygogd3Xmm0N9aLNsKX3EtkMs//PQkpomlahJkoKiFUGRGQDWZ2USP4ZVFMAc7drMRIBICQhafNn2g3of2vsvz+Gmc2rr/N36x/5TfEVf/swF/PcYXlPZP6na/QyYaTVgMBi6mDZNJEIvAC6KAtUza4oAZTmo67ooCm1EYrq4uBCRuq7NbD6fv3379vj4uAtBdlP0C8S96zb6KS8DyCu0+cwGxDAcVgd7e0+eHOzv71dlQMTVarW4v5UmmqTx+Koqw/XF9ccf3t1O58sVIKMiFUU12t0fjUZlFQriEe+mlFZNvVzWjDMA0NUquieQkQk8cdOTqXxbCP0yht69tecAAgC2yWDLWKjbaQS/VveVAPqu4hdErv+Bv0Iov2KlGYHZ/0E6vvMsM7MxkdP6iiSAlvgk5y4DgprZolmxRxsJUkrX19fYEpsOBoODgwPne4Tekv3/oH++zOUpSoYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=250x250 at 0x7FEA086702E8>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 打开原图\n",
    "test_img = Image.open(image_path)\n",
    "test_img"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 图片预处理"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 进行图片预处理\n",
    "test_img = np.array(test_img)\n",
    "img_size = np.asarray(test_img.shape)[0:2]\n",
    "factor_count=0\n",
    "minsize = 20\n",
    "total_boxes=np.empty((0,9))\n",
    "points=np.empty(0)\n",
    "h=test_img.shape[0] # h=410\n",
    "w=test_img.shape[1] # w=599\n",
    "\n",
    "minl=np.amin([h, w]) # minl = [410,599] 中最小值 410\n",
    "m=12.0/minsize # m=12/20\n",
    "minl=minl*m # minl = 410*12/20 = 410* 0.6 \n",
    "factor = 0.709 \n",
    "scales=[]\n",
    "\n",
    "while minl>=12:\n",
    "    scales += [m*np.power(factor, factor_count)]\n",
    "    minl = minl*factor \n",
    "    factor_count += 1\n",
    "\n",
    "# first stage\n",
    "for scale in scales:\n",
    "    hs=int(np.ceil(h*scale)) #大于等于该值的最小整数\n",
    "    ws=int(np.ceil(w*scale))\n",
    "    im_data = cv2.resize(test_img, (ws, hs), interpolation=cv2.INTER_AREA)\n",
    "    im_data = (im_data-127.5)*0.0078125\n",
    "    img_x = np.expand_dims(im_data, 0)\n",
    "    img_y = np.transpose(img_x, (0,2,1,3))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 运行PNet\n",
    "\n",
    "运行PNet，并加载预训练权重"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PNet产生结果为：(4, 9)\n"
     ]
    }
   ],
   "source": [
    "with tf.Graph().as_default():\n",
    "    with tf.Session() as sess:\n",
    "        with tf.variable_scope('pnet'):\n",
    "            data = tf.placeholder(tf.float32, shape=(None, None, None, 3), name=\"input\")\n",
    "            pnet = PNet({'data':data})\n",
    "            pnet.load(\"./src/align/PNet.npy\", sess)\n",
    "            out = sess.run(('pnet/conv4-2/BiasAdd:0', 'pnet/prob1:0'), feed_dict={'pnet/input:0':img_y})\n",
    "            \n",
    "#  boundingbox regression 结果 \n",
    "out0 = np.transpose(out[0], (0,2,1,3))\n",
    "#  face classification 结果\n",
    "out1 = np.transpose(out[1], (0,2,1,3))\n",
    "\n",
    "threshold = 0.5\n",
    "boxes, reg = generateBoundingBox(out1[0,:,:,1].copy(), out0[0,:,:,:].copy(), scale, threshold)\n",
    "print(\"PNet产生结果为：\"+str(boxes.shape))\n",
    "            \n",
    "total_boxes = boxes.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 边界框绘制函数\n",
    "def draw_bboxes(img, total_boxes):\n",
    "   \n",
    "    for i in range(total_boxes.shape[0]):\n",
    "        r = random.randint(0, 255)\n",
    "        g = random.randint(0, 255)\n",
    "        b = random.randint(0, 255)\n",
    "\n",
    "        x1 = int(total_boxes[:,0][i])\n",
    "        y1 =  int(total_boxes[:,1][i])\n",
    "        x2=  int(total_boxes[:,2][i])\n",
    "        y2 =  int(total_boxes[:,3][i])\n",
    "\n",
    "        img = cv2.rectangle(img,(x1,y1),(x2,y2), (r,g,b), 2)\n",
    "    \n",
    "    return img"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "将PNet预测结果进行筛选和回归，结果绘制在图片上"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "筛选之后结果为：(4, 9)\n",
      "(2, 9)\n",
      "(2, 5)\n",
      "[[ 20.70459607  41.49841332 216.40226045 237.1960777    0.95885891]\n",
      " [ 56.14747231  77.53658158 204.66903262 226.05814189   0.63998723]]\n",
      "[[ 20.          41.         216.         237.           0.95885891]\n",
      " [ 56.          77.         204.         226.           0.63998723]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=250x250 at 0x7FEA084B6F28>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "img = Image.open(image_path)\n",
    "img = np.array(img)\n",
    "Image.fromarray(draw_bboxes(img,total_boxes))\n",
    "total_boxes=np.empty((0,9))\n",
    "pick = nms(boxes.copy(), 0.7, 'Union')\n",
    "\n",
    "if boxes.size>0 and pick.size>0:\n",
    "    boxes = boxes[pick,:]\n",
    "    total_boxes = np.append(total_boxes, boxes, axis=0)\n",
    "print(\"筛选之后结果为：\"+str(total_boxes.shape))\n",
    "# 绘制筛选后的边界框\n",
    "img = Image.open(image_path)\n",
    "img = np.array(img)\n",
    "\n",
    "# 进行nms计算 参数为0.7\n",
    "pick = nms(total_boxes.copy(), 0.6, 'Union')\n",
    "total_boxes = total_boxes[pick,:]\n",
    "print(total_boxes.shape)\n",
    "\n",
    "# 边界框回归\n",
    "regw = total_boxes[:,2]-total_boxes[:,0]\n",
    "regh = total_boxes[:,3]-total_boxes[:,1]\n",
    "qq1 = total_boxes[:,0]+total_boxes[:,5]*regw\n",
    "qq2 = total_boxes[:,1]+total_boxes[:,6]*regh\n",
    "qq3 = total_boxes[:,2]+total_boxes[:,7]*regw\n",
    "qq4 = total_boxes[:,3]+total_boxes[:,8]*regh\n",
    "total_boxes = np.transpose(np.vstack([qq1, qq2, qq3, qq4, total_boxes[:,4]]))\n",
    "print(total_boxes.shape)\n",
    "img = Image.open(image_path)\n",
    "img = np.array(img)\n",
    "\n",
    "# 将边界框形状转为正方形\n",
    "total_boxes = rerec(total_boxes.copy())\n",
    "print(total_boxes)\n",
    "\n",
    "# 将边界框坐标整理成整数\n",
    "total_boxes[:,0:4] = np.fix(total_boxes[:,0:4]).astype(np.int32)\n",
    "print(total_boxes)\n",
    "dy, edy, dx, edx, y, ey, x, ex, tmpw, tmph = pad(total_boxes.copy(), w, h)\n",
    "\n",
    "img = Image.open(image_path)\n",
    "img = np.array(img)\n",
    "Image.fromarray(draw_bboxes(img,total_boxes))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 运行RNet\n",
    "\n",
    "MTCNN的PNet计算结束后，可以看到已经有若干个边界框已经被预测出来。接下来我们将进行RNet预测，通过RNet预测之后，边界框将更加准确。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 20.          41.         216.         237.           0.87911201]\n",
      " [ 56.          77.         204.         226.           0.61695826]]\n",
      "[[ 62.58686344  64.74073214 172.11160824 203.66461395   0.87911201]\n",
      " [ 64.44249545  69.13735405 164.18121961 193.78275371   0.61695826]]\n",
      "[[ 47.88729494  64.74073214 186.81117674 203.66461395   0.87911201]\n",
      " [ 51.9891577   69.13735405 176.63455736 193.78275371   0.61695826]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=250x250 at 0x7FEA084A7BE0>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "numbox = total_boxes.shape[0] \n",
    "tempimg = np.zeros((24,24,3,numbox))\n",
    "for k in range(0,numbox):\n",
    "    tmp = np.zeros((int(tmph[k]),int(tmpw[k]),3))\n",
    "    tmp[dy[k]-1:edy[k],dx[k]-1:edx[k],:] = img[y[k]-1:ey[k],x[k]-1:ex[k],:]\n",
    "    if tmp.shape[0]>0 and tmp.shape[1]>0 or tmp.shape[0]==0 and tmp.shape[1]==0:\n",
    "        tempimg[:,:,:,k] = imresample(tmp, (24, 24))\n",
    "    else:\n",
    "        print(0)\n",
    "tempimg = (tempimg-127.5)*0.0078125\n",
    "tempimg1 = np.transpose(tempimg, (3,1,0,2))\n",
    "with tf.Graph().as_default():\n",
    "    with tf.Session() as sess:\n",
    "        with tf.variable_scope('rnet'):\n",
    "            data = tf.placeholder(tf.float32, shape=(None, 24, 24, 3), name=\"input\")\n",
    "            rnet = RNet({'data':data})\n",
    "            rnet.load(\"./src/align/RNet.npy\", sess)\n",
    "            out = sess.run(('rnet/conv5-2/conv5-2:0', 'rnet/prob1:0'), feed_dict={'rnet/input:0':tempimg1})\n",
    "            \n",
    "# 检测到的人脸坐标\n",
    "out0 = np.transpose(out[0])\n",
    "out1 = np.transpose(out[1])\n",
    "\n",
    "score = out1[1,:]\n",
    "threshold = 0.7\n",
    "ipass = np.where(score>0.2)\n",
    "total_boxes = np.hstack([total_boxes[ipass[0],0:4].copy(), np.expand_dims(score[ipass].copy(),1)])\n",
    "mv = out0[:,ipass[0]]\n",
    "if total_boxes.shape[0]>0:\n",
    "    pick = nms(total_boxes, threshold, 'Union')\n",
    "    total_boxes = total_boxes[pick,:]\n",
    "    print(total_boxes)\n",
    "\n",
    "img = Image.open(image_path)\n",
    "img = np.array(img)\n",
    "    \n",
    "from src.align.detect_face import bbreg\n",
    "# 边界框回归\n",
    "total_boxes = bbreg(total_boxes.copy(), np.transpose(mv[:,pick]))\n",
    "print(total_boxes)\n",
    "# 边界框整理成正方形\n",
    "total_boxes = rerec(total_boxes.copy())\n",
    "print(total_boxes)\n",
    "\n",
    "img = Image.open(image_path)\n",
    "img = np.array(img)\n",
    "Image.fromarray(draw_bboxes(img,total_boxes))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 运行ONet\n",
    "\n",
    "最后，我们进行ONet预测，不仅使人脸的边界框检测更加准确，这一步还将关键点检测出来。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=250x250 at 0x7FEA082B5780>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "numbox = total_boxes.shape[0]\n",
    "total_boxes = np.fix(total_boxes).astype(np.int32)\n",
    "dy, edy, dx, edx, y, ey, x, ex, tmpw, tmph = pad(total_boxes.copy(), w, h)\n",
    "\n",
    "tempimg = np.zeros((48,48,3,numbox))\n",
    "for k in range(0,numbox):\n",
    "    tmp = np.zeros((int(tmph[k]),int(tmpw[k]),3))\n",
    "    tmp[dy[k]-1:edy[k],dx[k]-1:edx[k],:] = img[y[k]-1:ey[k],x[k]-1:ex[k],:]\n",
    "    if tmp.shape[0]>0 and tmp.shape[1]>0 or tmp.shape[0]==0 and tmp.shape[1]==0:\n",
    "        tempimg[:,:,:,k] = imresample(tmp, (48, 48))\n",
    "    else:\n",
    "        print(0)\n",
    "tempimg = (tempimg-127.5)*0.0078125\n",
    "tempimg1 = np.transpose(tempimg, (3,1,0,2))\n",
    "with tf.Graph().as_default():\n",
    "    with tf.Session() as sess:\n",
    "        with tf.variable_scope('onet'):\n",
    "            data = tf.placeholder(tf.float32, shape=(None, 48, 48, 3), name=\"input\")\n",
    "            onet = ONet({'data':data})\n",
    "            rnet.load(\"./src/align/ONet.npy\", sess)\n",
    "            out = sess.run(('onet/conv6-2/conv6-2:0', 'onet/conv6-3/conv6-3:0', 'onet/prob1:0'), feed_dict={'onet/input:0':tempimg1})\n",
    "            \n",
    "# 人脸区域边界框预测结果\n",
    "out0 = np.transpose(out[0])\n",
    "# 人脸关键点预测结果\n",
    "out1 = np.transpose(out[1])\n",
    "# 人脸区域置信度\n",
    "out2 = np.transpose(out[2])\n",
    "\n",
    "score = out2[1,:]\n",
    "points = out1\n",
    "# threshold = 0.7\n",
    "ipass = np.where(score>0.7)\n",
    "points = points[:,ipass[0]]\n",
    "total_boxes = np.hstack([total_boxes[ipass[0],0:4].copy(), np.expand_dims(score[ipass].copy(),1)])\n",
    "mv = out0[:,ipass[0]]\n",
    "\n",
    "w = total_boxes[:,2]-total_boxes[:,0]+1\n",
    "h = total_boxes[:,3]-total_boxes[:,1]+1\n",
    "points[0:5,:] = np.tile(w,(5, 1))*points[0:5,:] + np.tile(total_boxes[:,0],(5, 1))-1\n",
    "points[5:10,:] = np.tile(h,(5, 1))*points[5:10,:] + np.tile(total_boxes[:,1],(5, 1))-1\n",
    "if total_boxes.shape[0]>0:\n",
    "    total_boxes = bbreg(total_boxes.copy(), np.transpose(mv))\n",
    "    pick = nms(total_boxes.copy(), 0.7, 'Min')\n",
    "    total_boxes = total_boxes[pick,:]\n",
    "    points = points[:,pick]\n",
    "img = Image.open(image_path)\n",
    "img = np.array(img)\n",
    "\n",
    "r = random.randint(0, 255)\n",
    "g = random.randint(0, 255)\n",
    "b = random.randint(0, 255)\n",
    "\n",
    "point_color = (r, g, b) \n",
    "\n",
    "for i in range(5):\n",
    "    cv2.circle(img,(int(points[i]),int(points[i+5])),1, point_color, 4)\n",
    "    \n",
    "Image.fromarray(draw_bboxes(img,total_boxes))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 年龄预测\n",
    "\n",
    "我们使用`SSR-Net`模型预测年龄，该模型的论文见[此链接](https://www.ijcai.org/proceedings/2018/0150.pdf)。\n",
    "\n",
    "### 加载模型\n",
    "\n",
    "首先我们将模型结构和权重加载，预训练模型位置存储在`weight_file`中。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From /home/ma-user/anaconda3/envs/TensorFlow-1.13.1/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:3445: calling dropout (from tensorflow.python.ops.nn_ops) with keep_prob is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Please use `rate` instead of `keep_prob`. Rate should be set to `rate = 1 - keep_prob`.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From /home/ma-user/anaconda3/envs/TensorFlow-1.13.1/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:3445: calling dropout (from tensorflow.python.ops.nn_ops) with keep_prob is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Please use `rate` instead of `keep_prob`. Rate should be set to `rate = 1 - keep_prob`.\n"
     ]
    }
   ],
   "source": [
    "from SSRNET_model import SSR_net\n",
    "\n",
    "weight_file = \"./ssrnet_3_3_3_64_1.0_1.0.h5\"\n",
    "\n",
    "img_size = 64\n",
    "stage_num = [3,3,3]\n",
    "lambda_local = 1\n",
    "lambda_d = 1\n",
    "model = SSR_net(img_size,stage_num, lambda_local, lambda_d)()\n",
    "model.load_weights(weight_file)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "模型层级结构"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_1 (InputLayer)            (None, 64, 64, 3)    0                                            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_5 (Conv2D)               (None, 62, 62, 16)   448         input_1[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_1 (Conv2D)               (None, 62, 62, 32)   896         input_1[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_5 (BatchNor (None, 62, 62, 16)   64          conv2d_5[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_1 (BatchNor (None, 62, 62, 32)   128         conv2d_1[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_5 (Activation)       (None, 62, 62, 16)   0           batch_normalization_5[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "activation_1 (Activation)       (None, 62, 62, 32)   0           batch_normalization_1[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_1 (MaxPooling2D)  (None, 31, 31, 16)   0           activation_5[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_1 (AveragePoo (None, 31, 31, 32)   0           activation_1[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_6 (Conv2D)               (None, 29, 29, 16)   2320        max_pooling2d_1[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_2 (Conv2D)               (None, 29, 29, 32)   9248        average_pooling2d_1[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_6 (BatchNor (None, 29, 29, 16)   64          conv2d_6[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_2 (BatchNor (None, 29, 29, 32)   128         conv2d_2[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_6 (Activation)       (None, 29, 29, 16)   0           batch_normalization_6[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "activation_2 (Activation)       (None, 29, 29, 32)   0           batch_normalization_2[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_2 (MaxPooling2D)  (None, 14, 14, 16)   0           activation_6[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_2 (AveragePoo (None, 14, 14, 32)   0           activation_2[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_7 (Conv2D)               (None, 12, 12, 16)   2320        max_pooling2d_2[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_3 (Conv2D)               (None, 12, 12, 32)   9248        average_pooling2d_2[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_7 (BatchNor (None, 12, 12, 16)   64          conv2d_7[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_3 (BatchNor (None, 12, 12, 32)   128         conv2d_3[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_7 (Activation)       (None, 12, 12, 16)   0           batch_normalization_7[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "activation_3 (Activation)       (None, 12, 12, 32)   0           batch_normalization_3[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_3 (MaxPooling2D)  (None, 6, 6, 16)     0           activation_7[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_3 (AveragePoo (None, 6, 6, 32)     0           activation_3[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_8 (Conv2D)               (None, 4, 4, 16)     2320        max_pooling2d_3[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_4 (Conv2D)               (None, 4, 4, 32)     9248        average_pooling2d_3[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_8 (BatchNor (None, 4, 4, 16)     64          conv2d_8[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_4 (BatchNor (None, 4, 4, 32)     128         conv2d_4[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_8 (Activation)       (None, 4, 4, 16)     0           batch_normalization_8[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "activation_4 (Activation)       (None, 4, 4, 32)     0           batch_normalization_4[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_11 (Conv2D)              (None, 14, 14, 10)   170         max_pooling2d_2[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_12 (Conv2D)              (None, 14, 14, 10)   330         average_pooling2d_2[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_13 (Conv2D)              (None, 31, 31, 10)   170         max_pooling2d_1[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_14 (Conv2D)              (None, 31, 31, 10)   330         average_pooling2d_1[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_9 (Conv2D)               (None, 4, 4, 10)     170         activation_8[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_10 (Conv2D)              (None, 4, 4, 10)     330         activation_4[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_4 (MaxPooling2D)  (None, 3, 3, 10)     0           conv2d_11[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_4 (AveragePoo (None, 3, 3, 10)     0           conv2d_12[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_5 (MaxPooling2D)  (None, 3, 3, 10)     0           conv2d_13[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_5 (AveragePoo (None, 3, 3, 10)     0           conv2d_14[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "flatten_1 (Flatten)             (None, 160)          0           conv2d_9[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "flatten_2 (Flatten)             (None, 160)          0           conv2d_10[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "flatten_3 (Flatten)             (None, 90)           0           max_pooling2d_4[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "flatten_4 (Flatten)             (None, 90)           0           average_pooling2d_4[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "flatten_5 (Flatten)             (None, 90)           0           max_pooling2d_5[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "flatten_6 (Flatten)             (None, 90)           0           average_pooling2d_5[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "dropout_1 (Dropout)             (None, 160)          0           flatten_1[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "dropout_2 (Dropout)             (None, 160)          0           flatten_2[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "dropout_3 (Dropout)             (None, 90)           0           flatten_3[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "dropout_4 (Dropout)             (None, 90)           0           flatten_4[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "dropout_5 (Dropout)             (None, 90)           0           flatten_5[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "dropout_6 (Dropout)             (None, 90)           0           flatten_6[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "dense_1 (Dense)                 (None, 3)            483         dropout_1[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "dense_2 (Dense)                 (None, 3)            483         dropout_2[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "dense_4 (Dense)                 (None, 3)            273         dropout_3[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "dense_5 (Dense)                 (None, 3)            273         dropout_4[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "dense_7 (Dense)                 (None, 3)            273         dropout_5[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "dense_8 (Dense)                 (None, 3)            273         dropout_6[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "multiply_2 (Multiply)           (None, 3)            0           dense_1[0][0]                    \n",
      "                                                                 dense_2[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "multiply_4 (Multiply)           (None, 3)            0           dense_4[0][0]                    \n",
      "                                                                 dense_5[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "multiply_6 (Multiply)           (None, 3)            0           dense_7[0][0]                    \n",
      "                                                                 dense_8[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "dense_3 (Dense)                 (None, 6)            24          multiply_2[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "dense_6 (Dense)                 (None, 6)            24          multiply_4[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "dense_9 (Dense)                 (None, 6)            24          multiply_6[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "multiply_1 (Multiply)           (None, 160)          0           flatten_1[0][0]                  \n",
      "                                                                 flatten_2[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "multiply_3 (Multiply)           (None, 90)           0           flatten_3[0][0]                  \n",
      "                                                                 flatten_4[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "multiply_5 (Multiply)           (None, 90)           0           flatten_5[0][0]                  \n",
      "                                                                 flatten_6[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "pred_age_stage1 (Dense)         (None, 3)            21          dense_3[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "pred_age_stage2 (Dense)         (None, 3)            21          dense_6[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "pred_age_stage3 (Dense)         (None, 3)            21          dense_9[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "delta_s1 (Dense)                (None, 1)            161         multiply_1[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "delta_s2 (Dense)                (None, 1)            91          multiply_3[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "delta_s3 (Dense)                (None, 1)            91          multiply_5[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "local_delta_stage1 (Dense)      (None, 3)            21          dense_3[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "local_delta_stage2 (Dense)      (None, 3)            21          dense_6[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "local_delta_stage3 (Dense)      (None, 3)            21          dense_9[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "pred_a (Lambda)                 (None, 1)            0           pred_age_stage1[0][0]            \n",
      "                                                                 pred_age_stage2[0][0]            \n",
      "                                                                 pred_age_stage3[0][0]            \n",
      "                                                                 delta_s1[0][0]                   \n",
      "                                                                 delta_s2[0][0]                   \n",
      "                                                                 delta_s3[0][0]                   \n",
      "                                                                 local_delta_stage1[0][0]         \n",
      "                                                                 local_delta_stage2[0][0]         \n",
      "                                                                 local_delta_stage3[0][0]         \n",
      "==================================================================================================\n",
      "Total params: 40,915\n",
      "Trainable params: 40,531\n",
      "Non-trainable params: 384\n",
      "__________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "准备输入数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1, 64, 64, 3)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "faces = np.empty((len(detected), img_size, img_size, 3))\n",
    "faces.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 获取人脸区域图片，并缩放\n",
    "\n",
    "将人脸检测结果进行裁剪和缩放"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=64x64 at 0x7FE9945453C8>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ad = 0.4\n",
    "\n",
    "img_h, img_w, _ = np.shape(img)\n",
    "\n",
    "for i,d in enumerate(detected):\n",
    "    if d['confidence'] >=0.95 :\n",
    "        x1,y1,w,h = d['box']\n",
    "        x2 = x1 + w\n",
    "        y2 = y1 + h\n",
    "        xw1 = max(int(x1 - ad * w), 0)\n",
    "        yw1 = max(int(y1 - ad * h), 0)\n",
    "        xw2 = min(int(x2 + ad * w), img_w - 1)\n",
    "        yw2 = min(int(y2 + ad * h), img_h - 1)\n",
    "        img = cv2.resize(img[yw1:yw2+1, xw1:xw2+1, :], (img_size, img_size))\n",
    "        faces[i,:,:,:] = img\n",
    "        \n",
    "res_img = Image.fromarray(img)\n",
    "res_img"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 预测年龄\n",
    "\n",
    "将人脸区域图片输入模型，获得预测结果"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "res = model.predict(faces)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "预测年龄为：27\n"
     ]
    }
   ],
   "source": [
    "print(\"预测年龄为：\"+str(int(res[0])))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 小结\n",
    "\n",
    "在本实践中，我们详细解读并编码实现了人脸区域检测`MTCNN`模型，然后展示了如何使用`SSR-Net`模型预测年龄。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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